Overview

Dataset statistics

Number of variables465
Number of observations474
Missing cells192058
Missing cells (%)87.1%
Total size in memory8.3 MiB
Average record size in memory17.9 KiB

Variable types

Numeric1
Text299
Unsupported165

Alerts

selectioncriteria8_prog1 has constant value ""Constant
selectioncriteria7_prog2 has constant value ""Constant
priority3_prog3 has constant value ""Constant
priority1_prog4 has constant value ""Constant
priority2_prog4 has constant value ""Constant
selectioncriteria2_prog4 has constant value ""Constant
selectioncriteria3_prog4 has constant value ""Constant
selectioncriteria4_prog4 has constant value ""Constant
selectioncriteria5_prog4 has constant value ""Constant
selectioncriteria6_prog4 has constant value ""Constant
priority1_prog6 has constant value ""Constant
priority2_prog6 has constant value ""Constant
selectioncriteria2_prog7 has constant value ""Constant
selectioncriteria3_prog7 has constant value ""Constant
selectioncriteria4_prog7 has constant value ""Constant
selectioncriteria5_prog7 has constant value ""Constant
priority1_prog8 has constant value ""Constant
priority2_prog8 has constant value ""Constant
selectioncriteria2_prog8 has constant value ""Constant
selectioncriteria3_prog8 has constant value ""Constant
selectioncriteria4_prog8 has constant value ""Constant
selectioncriteria5_prog8 has constant value ""Constant
selectioncriteria6_prog8 has constant value ""Constant
selectioncriteria7_prog8 has constant value ""Constant
priority1_prog9 has constant value ""Constant
priority2_prog9 has constant value ""Constant
selectioncriteria2_prog9 has constant value ""Constant
selectioncriteria3_prog9 has constant value ""Constant
selectioncriteria4_prog9 has constant value ""Constant
selectioncriteria5_prog9 has constant value ""Constant
selectioncriteria6_prog9 has constant value ""Constant
selectioncriteria2_prog10 has constant value ""Constant
admissionsmethod_prog11 has constant value ""Constant
swdseats_prog11 has constant value ""Constant
gefilled_prog11 has constant value ""Constant
swdfilled_prog11 has constant value ""Constant
code_prog12 has constant value ""Constant
name_prog12 has constant value ""Constant
admissionsmethod_prog12 has constant value ""Constant
geapps_prog12 has constant value ""Constant
swdapps_prog12 has constant value ""Constant
geseats_prog12 has constant value ""Constant
swdseats_prog12 has constant value ""Constant
geappsperseat_prog12 has constant value ""Constant
swdappsperseat_prog12 has constant value ""Constant
gefilled_prog12 has constant value ""Constant
swdfilled_prog12 has constant value ""Constant
eligibility_prog12 has constant value ""Constant
selectioncriteria1_prog12 has constant value ""Constant
code_prog13 has constant value ""Constant
name_prog13 has constant value ""Constant
admissionsmethod_prog13 has constant value ""Constant
geapps_prog13 has constant value ""Constant
swdapps_prog13 has constant value ""Constant
geseats_prog13 has constant value ""Constant
swdseats_prog13 has constant value ""Constant
geappsperseat_prog13 has constant value ""Constant
swdappsperseat_prog13 has constant value ""Constant
gefilled_prog13 has constant value ""Constant
swdfilled_prog13 has constant value ""Constant
eligibility_prog13 has constant value ""Constant
selectioncriteria1_prog13 has constant value ""Constant
code_prog14 has constant value ""Constant
name_prog14 has constant value ""Constant
admissionsmethod_prog14 has constant value ""Constant
geapps_prog14 has constant value ""Constant
swdapps_prog14 has constant value ""Constant
geseats_prog14 has constant value ""Constant
swdseats_prog14 has constant value ""Constant
geappsperseat_prog14 has constant value ""Constant
swdappsperseat_prog14 has constant value ""Constant
gefilled_prog14 has constant value ""Constant
swdfilled_prog14 has constant value ""Constant
eligibility_prog14 has constant value ""Constant
selectioncriteria1_prog14 has constant value ""Constant
code_prog15 has constant value ""Constant
name_prog15 has constant value ""Constant
admissionsmethod_prog15 has constant value ""Constant
geapps_prog15 has constant value ""Constant
swdapps_prog15 has constant value ""Constant
geseats_prog15 has constant value ""Constant
swdseats_prog15 has constant value ""Constant
geappsperseat_prog15 has constant value ""Constant
swdappsperseat_prog15 has constant value ""Constant
gefilled_prog15 has constant value ""Constant
swdfilled_prog15 has constant value ""Constant
eligibility_prog15 has constant value ""Constant
neighborhood has 9 (1.9%) missing valuesMissing
independentwebsite has 204 (43.0%) missing valuesMissing
subway has 126 (26.6%) missing valuesMissing
bus has 9 (1.9%) missing valuesMissing
geapps_prog1 has 55 (11.6%) missing valuesMissing
swdapps_prog1 has 55 (11.6%) missing valuesMissing
geappsperseat_prog1 has 57 (12.0%) missing valuesMissing
swdappsperseat_prog1 has 67 (14.1%) missing valuesMissing
swdseats_prog1 has 55 (11.6%) missing valuesMissing
geseats_prog1 has 55 (11.6%) missing valuesMissing
gefilled_prog1 has 50 (10.5%) missing valuesMissing
swdfilled_prog1 has 50 (10.5%) missing valuesMissing
priority1_prog1 has 186 (39.2%) missing valuesMissing
priority2_prog1 has 186 (39.2%) missing valuesMissing
priority3_prog1 has 355 (74.9%) missing valuesMissing
priority4_prog1 has 422 (89.0%) missing valuesMissing
priority5_prog1 has 454 (95.8%) missing valuesMissing
priority6_prog1 has 462 (97.5%) missing valuesMissing
priority7_prog1 has 471 (99.4%) missing valuesMissing
prefnote_prog1 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog1 has 297 (62.7%) missing valuesMissing
selectioncriteria2_prog1 has 313 (66.0%) missing valuesMissing
selectioncriteria3_prog1 has 318 (67.1%) missing valuesMissing
selectioncriteria4_prog1 has 336 (70.9%) missing valuesMissing
selectioncriteria5_prog1 has 375 (79.1%) missing valuesMissing
selectioncriteria6_prog1 has 442 (93.2%) missing valuesMissing
selectioncriteria7_prog1 has 466 (98.3%) missing valuesMissing
selectioncriteria8_prog1 has 472 (99.6%) missing valuesMissing
code_prog2 has 299 (63.1%) missing valuesMissing
name_prog2 has 299 (63.1%) missing valuesMissing
admissionsmethod_prog2 has 299 (63.1%) missing valuesMissing
geapps_prog2 has 330 (69.6%) missing valuesMissing
swdapps_prog2 has 330 (69.6%) missing valuesMissing
geappsperseat_prog2 has 331 (69.8%) missing valuesMissing
swdappsperseat_prog2 has 331 (69.8%) missing valuesMissing
swdseats_prog2 has 330 (69.6%) missing valuesMissing
geseats_prog2 has 330 (69.6%) missing valuesMissing
gefilled_prog2 has 311 (65.6%) missing valuesMissing
swdfilled_prog2 has 311 (65.6%) missing valuesMissing
eligibility_prog2 has 300 (63.3%) missing valuesMissing
priority1_prog2 has 391 (82.5%) missing valuesMissing
priority2_prog2 has 394 (83.1%) missing valuesMissing
priority3_prog2 has 452 (95.4%) missing valuesMissing
priority4_prog2 has 463 (97.7%) missing valuesMissing
priority5_prog2 has 472 (99.6%) missing valuesMissing
priority6_prog2 has 474 (100.0%) missing valuesMissing
priority7_prog2 has 474 (100.0%) missing valuesMissing
prefnote_prog2 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog2 has 435 (91.8%) missing valuesMissing
selectioncriteria2_prog2 has 445 (93.9%) missing valuesMissing
selectioncriteria3_prog2 has 448 (94.5%) missing valuesMissing
selectioncriteria4_prog2 has 454 (95.8%) missing valuesMissing
selectioncriteria5_prog2 has 460 (97.0%) missing valuesMissing
selectioncriteria6_prog2 has 469 (98.9%) missing valuesMissing
selectioncriteria7_prog2 has 473 (99.8%) missing valuesMissing
selectioncriteria8_prog2 has 474 (100.0%) missing valuesMissing
code_prog3 has 415 (87.6%) missing valuesMissing
name_prog3 has 415 (87.6%) missing valuesMissing
admissionsmethod_prog3 has 415 (87.6%) missing valuesMissing
geapps_prog3 has 432 (91.1%) missing valuesMissing
swdapps_prog3 has 432 (91.1%) missing valuesMissing
geappsperseat_prog3 has 432 (91.1%) missing valuesMissing
swdappsperseat_prog3 has 432 (91.1%) missing valuesMissing
swdseats_prog3 has 432 (91.1%) missing valuesMissing
geseats_prog3 has 432 (91.1%) missing valuesMissing
gefilled_prog3 has 416 (87.8%) missing valuesMissing
swdfilled_prog3 has 416 (87.8%) missing valuesMissing
eligibility_prog3 has 415 (87.6%) missing valuesMissing
priority1_prog3 has 461 (97.3%) missing valuesMissing
priority2_prog3 has 461 (97.3%) missing valuesMissing
priority3_prog3 has 467 (98.5%) missing valuesMissing
priority4_prog3 has 474 (100.0%) missing valuesMissing
priority5_prog3 has 474 (100.0%) missing valuesMissing
priority6_prog3 has 474 (100.0%) missing valuesMissing
priority7_prog3 has 474 (100.0%) missing valuesMissing
prefnote_prog3 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog3 has 462 (97.5%) missing valuesMissing
selectioncriteria2_prog3 has 468 (98.7%) missing valuesMissing
selectioncriteria3_prog3 has 468 (98.7%) missing valuesMissing
selectioncriteria4_prog3 has 468 (98.7%) missing valuesMissing
selectioncriteria5_prog3 has 468 (98.7%) missing valuesMissing
selectioncriteria6_prog3 has 472 (99.6%) missing valuesMissing
selectioncriteria7_prog3 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog3 has 474 (100.0%) missing valuesMissing
code_prog4 has 449 (94.7%) missing valuesMissing
name_prog4 has 449 (94.7%) missing valuesMissing
admissionsmethod_prog4 has 449 (94.7%) missing valuesMissing
geapps_prog4 has 459 (96.8%) missing valuesMissing
swdapps_prog4 has 459 (96.8%) missing valuesMissing
geappsperseat_prog4 has 459 (96.8%) missing valuesMissing
swdappsperseat_prog4 has 459 (96.8%) missing valuesMissing
swdseats_prog4 has 459 (96.8%) missing valuesMissing
geseats_prog4 has 459 (96.8%) missing valuesMissing
gefilled_prog4 has 451 (95.1%) missing valuesMissing
swdfilled_prog4 has 451 (95.1%) missing valuesMissing
eligibility_prog4 has 449 (94.7%) missing valuesMissing
priority1_prog4 has 473 (99.8%) missing valuesMissing
priority2_prog4 has 473 (99.8%) missing valuesMissing
priority3_prog4 has 474 (100.0%) missing valuesMissing
priority4_prog4 has 474 (100.0%) missing valuesMissing
priority5_prog4 has 474 (100.0%) missing valuesMissing
priority6_prog4 has 474 (100.0%) missing valuesMissing
priority7_prog4 has 474 (100.0%) missing valuesMissing
prefnote_prog4 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog4 has 468 (98.7%) missing valuesMissing
selectioncriteria2_prog4 has 473 (99.8%) missing valuesMissing
selectioncriteria3_prog4 has 473 (99.8%) missing valuesMissing
selectioncriteria4_prog4 has 473 (99.8%) missing valuesMissing
selectioncriteria5_prog4 has 473 (99.8%) missing valuesMissing
selectioncriteria6_prog4 has 473 (99.8%) missing valuesMissing
selectioncriteria7_prog4 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog4 has 474 (100.0%) missing valuesMissing
code_prog5 has 463 (97.7%) missing valuesMissing
name_prog5 has 463 (97.7%) missing valuesMissing
admissionsmethod_prog5 has 463 (97.7%) missing valuesMissing
geapps_prog5 has 465 (98.1%) missing valuesMissing
swdapps_prog5 has 465 (98.1%) missing valuesMissing
geappsperseat_prog5 has 465 (98.1%) missing valuesMissing
swdappsperseat_prog5 has 465 (98.1%) missing valuesMissing
swdseats_prog5 has 465 (98.1%) missing valuesMissing
geseats_prog5 has 465 (98.1%) missing valuesMissing
gefilled_prog5 has 464 (97.9%) missing valuesMissing
swdfilled_prog5 has 464 (97.9%) missing valuesMissing
eligibility_prog5 has 463 (97.7%) missing valuesMissing
priority1_prog5 has 474 (100.0%) missing valuesMissing
priority2_prog5 has 474 (100.0%) missing valuesMissing
priority3_prog5 has 474 (100.0%) missing valuesMissing
priority4_prog5 has 474 (100.0%) missing valuesMissing
priority5_prog5 has 474 (100.0%) missing valuesMissing
priority6_prog5 has 474 (100.0%) missing valuesMissing
priority7_prog5 has 474 (100.0%) missing valuesMissing
prefnote_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog5 has 469 (98.9%) missing valuesMissing
selectioncriteria2_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog5 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog5 has 474 (100.0%) missing valuesMissing
code_prog6 has 468 (98.7%) missing valuesMissing
name_prog6 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog6 has 468 (98.7%) missing valuesMissing
geapps_prog6 has 468 (98.7%) missing valuesMissing
swdapps_prog6 has 468 (98.7%) missing valuesMissing
geappsperseat_prog6 has 468 (98.7%) missing valuesMissing
swdappsperseat_prog6 has 468 (98.7%) missing valuesMissing
swdseats_prog6 has 468 (98.7%) missing valuesMissing
geseats_prog6 has 468 (98.7%) missing valuesMissing
gefilled_prog6 has 468 (98.7%) missing valuesMissing
swdfilled_prog6 has 468 (98.7%) missing valuesMissing
eligibility_prog6 has 468 (98.7%) missing valuesMissing
priority1_prog6 has 473 (99.8%) missing valuesMissing
priority2_prog6 has 473 (99.8%) missing valuesMissing
priority3_prog6 has 474 (100.0%) missing valuesMissing
priority4_prog6 has 474 (100.0%) missing valuesMissing
priority5_prog6 has 474 (100.0%) missing valuesMissing
priority6_prog6 has 474 (100.0%) missing valuesMissing
priority7_prog6 has 474 (100.0%) missing valuesMissing
prefnote_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria1_prog6 has 469 (98.9%) missing valuesMissing
selectioncriteria2_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog6 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog6 has 474 (100.0%) missing valuesMissing
code_prog7 has 468 (98.7%) missing valuesMissing
name_prog7 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog7 has 468 (98.7%) missing valuesMissing
geapps_prog7 has 468 (98.7%) missing valuesMissing
swdapps_prog7 has 468 (98.7%) missing valuesMissing
geseats_prog7 has 468 (98.7%) missing valuesMissing
swdseats_prog7 has 468 (98.7%) missing valuesMissing
geappsperseat_prog7 has 468 (98.7%) missing valuesMissing
swdappsperseat_prog7 has 468 (98.7%) missing valuesMissing
gefilled_prog7 has 468 (98.7%) missing valuesMissing
swdfilled_prog7 has 468 (98.7%) missing valuesMissing
prefnote_prog7 has 474 (100.0%) missing valuesMissing
priority1_prog7 has 474 (100.0%) missing valuesMissing
priority2_prog7 has 474 (100.0%) missing valuesMissing
priority3_prog7 has 474 (100.0%) missing valuesMissing
priority4_prog7 has 474 (100.0%) missing valuesMissing
priority5_prog7 has 474 (100.0%) missing valuesMissing
priority6_prog7 has 474 (100.0%) missing valuesMissing
priority7_prog7 has 474 (100.0%) missing valuesMissing
eligibility_prog7 has 468 (98.7%) missing valuesMissing
selectioncriteria1_prog7 has 468 (98.7%) missing valuesMissing
selectioncriteria2_prog7 has 473 (99.8%) missing valuesMissing
selectioncriteria3_prog7 has 473 (99.8%) missing valuesMissing
selectioncriteria4_prog7 has 473 (99.8%) missing valuesMissing
selectioncriteria5_prog7 has 473 (99.8%) missing valuesMissing
selectioncriteria6_prog7 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog7 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog7 has 474 (100.0%) missing valuesMissing
code_prog8 has 468 (98.7%) missing valuesMissing
name_prog8 has 468 (98.7%) missing valuesMissing
admissionsmethod_prog8 has 468 (98.7%) missing valuesMissing
geapps_prog8 has 469 (98.9%) missing valuesMissing
swdapps_prog8 has 469 (98.9%) missing valuesMissing
geseats_prog8 has 469 (98.9%) missing valuesMissing
swdseats_prog8 has 469 (98.9%) missing valuesMissing
geappsperseat_prog8 has 469 (98.9%) missing valuesMissing
swdappsperseat_prog8 has 469 (98.9%) missing valuesMissing
gefilled_prog8 has 468 (98.7%) missing valuesMissing
swdfilled_prog8 has 468 (98.7%) missing valuesMissing
prefnote_prog8 has 474 (100.0%) missing valuesMissing
priority1_prog8 has 473 (99.8%) missing valuesMissing
priority2_prog8 has 473 (99.8%) missing valuesMissing
priority3_prog8 has 474 (100.0%) missing valuesMissing
priority4_prog8 has 474 (100.0%) missing valuesMissing
priority5_prog8 has 474 (100.0%) missing valuesMissing
priority6_prog8 has 474 (100.0%) missing valuesMissing
priority7_prog8 has 474 (100.0%) missing valuesMissing
eligibility_prog8 has 468 (98.7%) missing valuesMissing
selectioncriteria1_prog8 has 470 (99.2%) missing valuesMissing
selectioncriteria2_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria3_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria4_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria5_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria6_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria7_prog8 has 473 (99.8%) missing valuesMissing
selectioncriteria8_prog8 has 474 (100.0%) missing valuesMissing
code_prog9 has 469 (98.9%) missing valuesMissing
name_prog9 has 469 (98.9%) missing valuesMissing
admissionsmethod_prog9 has 469 (98.9%) missing valuesMissing
geapps_prog9 has 469 (98.9%) missing valuesMissing
swdapps_prog9 has 469 (98.9%) missing valuesMissing
geseats_prog9 has 469 (98.9%) missing valuesMissing
swdseats_prog9 has 469 (98.9%) missing valuesMissing
geappsperseat_prog9 has 469 (98.9%) missing valuesMissing
swdappsperseat_prog9 has 469 (98.9%) missing valuesMissing
gefilled_prog9 has 469 (98.9%) missing valuesMissing
swdfilled_prog9 has 469 (98.9%) missing valuesMissing
prefnote_prog9 has 474 (100.0%) missing valuesMissing
priority1_prog9 has 473 (99.8%) missing valuesMissing
priority2_prog9 has 473 (99.8%) missing valuesMissing
priority3_prog9 has 474 (100.0%) missing valuesMissing
priority4_prog9 has 474 (100.0%) missing valuesMissing
priority5_prog9 has 474 (100.0%) missing valuesMissing
priority6_prog9 has 474 (100.0%) missing valuesMissing
priority7_prog9 has 474 (100.0%) missing valuesMissing
eligibility_prog9 has 469 (98.9%) missing valuesMissing
selectioncriteria1_prog9 has 470 (99.2%) missing valuesMissing
selectioncriteria2_prog9 has 473 (99.8%) missing valuesMissing
selectioncriteria3_prog9 has 473 (99.8%) missing valuesMissing
selectioncriteria4_prog9 has 473 (99.8%) missing valuesMissing
selectioncriteria5_prog9 has 473 (99.8%) missing valuesMissing
selectioncriteria6_prog9 has 473 (99.8%) missing valuesMissing
selectioncriteria7_prog9 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog9 has 474 (100.0%) missing valuesMissing
code_prog10 has 470 (99.2%) missing valuesMissing
name_prog10 has 470 (99.2%) missing valuesMissing
admissionsmethod_prog10 has 470 (99.2%) missing valuesMissing
geapps_prog10 has 470 (99.2%) missing valuesMissing
swdapps_prog10 has 470 (99.2%) missing valuesMissing
geseats_prog10 has 470 (99.2%) missing valuesMissing
swdseats_prog10 has 470 (99.2%) missing valuesMissing
geappsperseat_prog10 has 470 (99.2%) missing valuesMissing
swdappsperseat_prog10 has 471 (99.4%) missing valuesMissing
gefilled_prog10 has 470 (99.2%) missing valuesMissing
swdfilled_prog10 has 470 (99.2%) missing valuesMissing
prefnote_prog10 has 474 (100.0%) missing valuesMissing
priority1_prog10 has 474 (100.0%) missing valuesMissing
priority2_prog10 has 474 (100.0%) missing valuesMissing
priority3_prog10 has 474 (100.0%) missing valuesMissing
priority4_prog10 has 474 (100.0%) missing valuesMissing
priority5_prog10 has 474 (100.0%) missing valuesMissing
priority6_prog10 has 474 (100.0%) missing valuesMissing
priority7_prog10 has 474 (100.0%) missing valuesMissing
eligibility_prog10 has 470 (99.2%) missing valuesMissing
selectioncriteria1_prog10 has 470 (99.2%) missing valuesMissing
selectioncriteria2_prog10 has 473 (99.8%) missing valuesMissing
selectioncriteria3_prog10 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog10 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog10 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog10 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog10 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog10 has 474 (100.0%) missing valuesMissing
code_prog11 has 472 (99.6%) missing valuesMissing
name_prog11 has 472 (99.6%) missing valuesMissing
admissionsmethod_prog11 has 472 (99.6%) missing valuesMissing
geapps_prog11 has 472 (99.6%) missing valuesMissing
swdapps_prog11 has 472 (99.6%) missing valuesMissing
geseats_prog11 has 472 (99.6%) missing valuesMissing
swdseats_prog11 has 472 (99.6%) missing valuesMissing
geappsperseat_prog11 has 472 (99.6%) missing valuesMissing
swdappsperseat_prog11 has 472 (99.6%) missing valuesMissing
gefilled_prog11 has 472 (99.6%) missing valuesMissing
swdfilled_prog11 has 472 (99.6%) missing valuesMissing
prefnote_prog11 has 474 (100.0%) missing valuesMissing
priority1_prog11 has 474 (100.0%) missing valuesMissing
priority2_prog11 has 474 (100.0%) missing valuesMissing
priority3_prog11 has 474 (100.0%) missing valuesMissing
priority4_prog11 has 474 (100.0%) missing valuesMissing
priority5_prog11 has 474 (100.0%) missing valuesMissing
priority6_prog11 has 474 (100.0%) missing valuesMissing
priority7_prog11 has 474 (100.0%) missing valuesMissing
eligibility_prog11 has 472 (99.6%) missing valuesMissing
selectioncriteria1_prog11 has 472 (99.6%) missing valuesMissing
selectioncriteria2_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog11 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog11 has 474 (100.0%) missing valuesMissing
code_prog12 has 473 (99.8%) missing valuesMissing
name_prog12 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog12 has 473 (99.8%) missing valuesMissing
geapps_prog12 has 473 (99.8%) missing valuesMissing
swdapps_prog12 has 473 (99.8%) missing valuesMissing
geseats_prog12 has 473 (99.8%) missing valuesMissing
swdseats_prog12 has 473 (99.8%) missing valuesMissing
geappsperseat_prog12 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog12 has 473 (99.8%) missing valuesMissing
gefilled_prog12 has 473 (99.8%) missing valuesMissing
swdfilled_prog12 has 473 (99.8%) missing valuesMissing
prefnote_prog12 has 474 (100.0%) missing valuesMissing
priority1_prog12 has 474 (100.0%) missing valuesMissing
priority2_prog12 has 474 (100.0%) missing valuesMissing
priority3_prog12 has 474 (100.0%) missing valuesMissing
priority4_prog12 has 474 (100.0%) missing valuesMissing
priority5_prog12 has 474 (100.0%) missing valuesMissing
priority6_prog12 has 474 (100.0%) missing valuesMissing
priority7_prog12 has 474 (100.0%) missing valuesMissing
eligibility_prog12 has 473 (99.8%) missing valuesMissing
selectioncriteria1_prog12 has 473 (99.8%) missing valuesMissing
selectioncriteria2_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog12 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog12 has 474 (100.0%) missing valuesMissing
code_prog13 has 473 (99.8%) missing valuesMissing
name_prog13 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog13 has 473 (99.8%) missing valuesMissing
geapps_prog13 has 473 (99.8%) missing valuesMissing
swdapps_prog13 has 473 (99.8%) missing valuesMissing
geseats_prog13 has 473 (99.8%) missing valuesMissing
swdseats_prog13 has 473 (99.8%) missing valuesMissing
geappsperseat_prog13 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog13 has 473 (99.8%) missing valuesMissing
gefilled_prog13 has 473 (99.8%) missing valuesMissing
swdfilled_prog13 has 473 (99.8%) missing valuesMissing
prefnote_prog13 has 474 (100.0%) missing valuesMissing
priority1_prog13 has 474 (100.0%) missing valuesMissing
priority2_prog13 has 474 (100.0%) missing valuesMissing
priority3_prog13 has 474 (100.0%) missing valuesMissing
priority4_prog13 has 474 (100.0%) missing valuesMissing
priority5_prog13 has 474 (100.0%) missing valuesMissing
priority6_prog13 has 474 (100.0%) missing valuesMissing
priority7_prog13 has 474 (100.0%) missing valuesMissing
eligibility_prog13 has 473 (99.8%) missing valuesMissing
selectioncriteria1_prog13 has 473 (99.8%) missing valuesMissing
selectioncriteria2_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog13 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog13 has 474 (100.0%) missing valuesMissing
code_prog14 has 473 (99.8%) missing valuesMissing
name_prog14 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog14 has 473 (99.8%) missing valuesMissing
geapps_prog14 has 473 (99.8%) missing valuesMissing
swdapps_prog14 has 473 (99.8%) missing valuesMissing
geseats_prog14 has 473 (99.8%) missing valuesMissing
swdseats_prog14 has 473 (99.8%) missing valuesMissing
geappsperseat_prog14 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog14 has 473 (99.8%) missing valuesMissing
gefilled_prog14 has 473 (99.8%) missing valuesMissing
swdfilled_prog14 has 473 (99.8%) missing valuesMissing
prefnote_prog14 has 474 (100.0%) missing valuesMissing
priority1_prog14 has 474 (100.0%) missing valuesMissing
priority2_prog14 has 474 (100.0%) missing valuesMissing
priority3_prog14 has 474 (100.0%) missing valuesMissing
priority4_prog14 has 474 (100.0%) missing valuesMissing
priority5_prog14 has 474 (100.0%) missing valuesMissing
priority6_prog14 has 474 (100.0%) missing valuesMissing
priority7_prog14 has 474 (100.0%) missing valuesMissing
eligibility_prog14 has 473 (99.8%) missing valuesMissing
selectioncriteria1_prog14 has 473 (99.8%) missing valuesMissing
selectioncriteria2_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog14 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog14 has 474 (100.0%) missing valuesMissing
code_prog15 has 473 (99.8%) missing valuesMissing
name_prog15 has 473 (99.8%) missing valuesMissing
admissionsmethod_prog15 has 473 (99.8%) missing valuesMissing
geapps_prog15 has 473 (99.8%) missing valuesMissing
swdapps_prog15 has 473 (99.8%) missing valuesMissing
geseats_prog15 has 473 (99.8%) missing valuesMissing
swdseats_prog15 has 473 (99.8%) missing valuesMissing
geappsperseat_prog15 has 473 (99.8%) missing valuesMissing
swdappsperseat_prog15 has 473 (99.8%) missing valuesMissing
gefilled_prog15 has 473 (99.8%) missing valuesMissing
swdfilled_prog15 has 473 (99.8%) missing valuesMissing
prefnote_prog15 has 474 (100.0%) missing valuesMissing
priority1_prog15 has 474 (100.0%) missing valuesMissing
priority2_prog15 has 474 (100.0%) missing valuesMissing
priority3_prog15 has 474 (100.0%) missing valuesMissing
priority4_prog15 has 474 (100.0%) missing valuesMissing
priority5_prog15 has 474 (100.0%) missing valuesMissing
priority6_prog15 has 474 (100.0%) missing valuesMissing
priority7_prog15 has 474 (100.0%) missing valuesMissing
eligibility_prog15 has 473 (99.8%) missing valuesMissing
selectioncriteria1_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria2_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria3_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria4_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria5_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria6_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria7_prog15 has 474 (100.0%) missing valuesMissing
selectioncriteria8_prog15 has 474 (100.0%) missing valuesMissing
coursepassrate has 10 (2.1%) missing valuesMissing
elaprof has 13 (2.7%) missing valuesMissing
mathprof has 13 (2.7%) missing valuesMissing
tophs1 has 12 (2.5%) missing valuesMissing
tophs2 has 110 (23.2%) missing valuesMissing
tophs3 has 269 (56.8%) missing valuesMissing
surveysafety has 9 (1.9%) missing valuesMissing
diversityinadmissions has 442 (93.2%) missing valuesMissing
start_time has 10 (2.1%) missing valuesMissing
end_time has 12 (2.5%) missing valuesMissing
other_features has 162 (34.2%) missing valuesMissing
languageclasses has 115 (24.3%) missing valuesMissing
acceleratedclasses has 98 (20.7%) missing valuesMissing
electiveclasses has 474 (100.0%) missing valuesMissing
activities has 127 (26.8%) missing valuesMissing
champsboys has 441 (93.0%) missing valuesMissing
champsgirls has 426 (89.9%) missing valuesMissing
champscoed has 247 (52.1%) missing valuesMissing
othersports has 128 (27.0%) missing valuesMissing
0 has unique valuesUnique
schooldbn has unique valuesUnique
name has unique valuesUnique
overview has unique valuesUnique
code_prog1 has unique valuesUnique
prefnote_prog1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog9 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
prefnote_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority1_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority2_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority3_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority4_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority5_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority6_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
priority7_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria1_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria2_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria3_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria4_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria5_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria6_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria7_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
selectioncriteria8_prog15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
electiveclasses is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-09 22:38:25.056943
Analysis finished2023-12-09 22:38:36.818112
Duration11.76 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

0
Real number (ℝ)

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean237.5
Minimum1
Maximum474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2023-12-09T22:38:37.357307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile24.65
Q1119.25
median237.5
Q3355.75
95-th percentile450.35
Maximum474
Range473
Interquartile range (IQR)236.5

Descriptive statistics

Standard deviation136.9762753
Coefficient of variation (CV)0.5767422119
Kurtosis-1.2
Mean237.5
Median Absolute Deviation (MAD)118.5
Skewness0
Sum112575
Variance18762.5
MonotonicityStrictly increasing
2023-12-09T22:38:37.523809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
312 1
 
0.2%
324 1
 
0.2%
323 1
 
0.2%
322 1
 
0.2%
321 1
 
0.2%
320 1
 
0.2%
319 1
 
0.2%
318 1
 
0.2%
317 1
 
0.2%
Other values (464) 464
97.9%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
ValueCountFrequency (%)
474 1
0.2%
473 1
0.2%
472 1
0.2%
471 1
0.2%
470 1
0.2%

district
Text

Distinct32
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size27.3 KiB
2023-12-09T22:38:38.065588image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.683544304
Min length1

Characters and Unicode

Total characters798
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
9 26
 
5.5%
10 26
 
5.5%
2 23
 
4.9%
27 23
 
4.9%
11 20
 
4.2%
3 19
 
4.0%
6 19
 
4.0%
19 17
 
3.6%
29 17
 
3.6%
8 16
 
3.4%
Other values (22) 268
56.5%
2023-12-09T22:38:38.508404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 201
25.2%
1 200
25.1%
3 82
10.3%
9 60
 
7.5%
0 58
 
7.3%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 798
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 201
25.2%
1 200
25.1%
3 82
10.3%
9 60
 
7.5%
0 58
 
7.3%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 798
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 201
25.2%
1 200
25.1%
3 82
10.3%
9 60
 
7.5%
0 58
 
7.3%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 798
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 201
25.2%
1 200
25.1%
3 82
10.3%
9 60
 
7.5%
0 58
 
7.3%
7 52
 
6.5%
8 38
 
4.8%
4 38
 
4.8%
5 37
 
4.6%
6 32
 
4.0%

schooldbn
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size29.3 KiB
2023-12-09T22:38:38.960920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2844
Distinct characters15
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st row01M034
2nd row01M140
3rd row01M184
4th row01M188
5th row01M332
ValueCountFrequency (%)
20k609 1
 
0.2%
10x037 1
 
0.2%
29q116 1
 
0.2%
06m324 1
 
0.2%
19k364 1
 
0.2%
13k527 1
 
0.2%
02m255 1
 
0.2%
27q146 1
 
0.2%
03m421 1
 
0.2%
09x505 1
 
0.2%
Other values (464) 464
97.9%
2023-12-09T22:38:39.550913image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 428
15.0%
1 393
13.8%
0 378
13.3%
3 253
8.9%
4 167
 
5.9%
8 161
 
5.7%
9 155
 
5.5%
7 148
 
5.2%
5 144
 
5.1%
K 143
 
5.0%
Other values (5) 474
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2370
83.3%
Uppercase Letter 474
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 428
18.1%
1 393
16.6%
0 378
15.9%
3 253
10.7%
4 167
 
7.0%
8 161
 
6.8%
9 155
 
6.5%
7 148
 
6.2%
5 144
 
6.1%
6 143
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
K 143
30.2%
X 116
24.5%
Q 105
22.2%
M 95
20.0%
R 15
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2370
83.3%
Latin 474
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 428
18.1%
1 393
16.6%
0 378
15.9%
3 253
10.7%
4 167
 
7.0%
8 161
 
6.8%
9 155
 
6.5%
7 148
 
6.2%
5 144
 
6.1%
6 143
 
6.0%
Latin
ValueCountFrequency (%)
K 143
30.2%
X 116
24.5%
Q 105
22.2%
M 95
20.0%
R 15
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2844
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 428
15.0%
1 393
13.8%
0 378
13.3%
3 253
8.9%
4 167
 
5.9%
8 161
 
5.7%
9 155
 
5.5%
7 148
 
5.2%
5 144
 
5.1%
K 143
 
5.0%
Other values (5) 474
16.7%

name
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
2023-12-09T22:38:39.907549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length87
Median length65
Mean length38.32489451
Min length14

Characters and Unicode

Total characters18166
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st rowP.S. 034 Franklin D. Roosevelt (01M034)
2nd rowP.S. 140 Nathan Straus (01M140)
3rd rowP.S. 184m Shuang Wen (01M184)
4th rowP.S. 188 The Island School (01M188)
5th rowUniversity Neighborhood Middle School (01M332)
ValueCountFrequency (%)
school 182
 
6.7%
academy 73
 
2.7%
p.s 73
 
2.7%
the 69
 
2.5%
i.s 64
 
2.3%
middle 56
 
2.0%
for 55
 
2.0%
j.h.s 43
 
1.6%
of 40
 
1.5%
m.s 39
 
1.4%
Other values (1349) 2038
74.6%
2023-12-09T22:38:40.453062image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2260
 
12.4%
e 992
 
5.5%
o 961
 
5.3%
a 703
 
3.9%
. 673
 
3.7%
l 649
 
3.6%
r 595
 
3.3%
S 584
 
3.2%
n 566
 
3.1%
2 554
 
3.0%
Other values (64) 9629
53.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8274
45.5%
Decimal Number 3139
 
17.3%
Uppercase Letter 2737
 
15.1%
Space Separator 2260
 
12.4%
Other Punctuation 765
 
4.2%
Close Punctuation 486
 
2.7%
Open Punctuation 486
 
2.7%
Dash Punctuation 18
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 992
12.0%
o 961
11.6%
a 703
 
8.5%
l 649
 
7.8%
r 595
 
7.2%
n 566
 
6.8%
i 496
 
6.0%
c 451
 
5.5%
h 426
 
5.1%
t 409
 
4.9%
Other values (16) 2026
24.5%
Uppercase Letter
ValueCountFrequency (%)
S 584
21.3%
M 301
11.0%
P 183
 
6.7%
A 174
 
6.4%
K 159
 
5.8%
I 141
 
5.2%
X 123
 
4.5%
Q 114
 
4.2%
C 112
 
4.1%
H 109
 
4.0%
Other values (16) 737
26.9%
Decimal Number
ValueCountFrequency (%)
2 554
17.6%
1 532
16.9%
0 489
15.6%
3 330
10.5%
8 228
7.3%
4 226
7.2%
9 208
 
6.6%
7 200
 
6.4%
5 191
 
6.1%
6 181
 
5.8%
Other Punctuation
ValueCountFrequency (%)
. 673
88.0%
/ 39
 
5.1%
& 18
 
2.4%
, 17
 
2.2%
: 10
 
1.3%
' 7
 
0.9%
\ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2260
100.0%
Close Punctuation
ValueCountFrequency (%)
) 486
100.0%
Open Punctuation
ValueCountFrequency (%)
( 486
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11011
60.6%
Common 7155
39.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 992
 
9.0%
o 961
 
8.7%
a 703
 
6.4%
l 649
 
5.9%
r 595
 
5.4%
S 584
 
5.3%
n 566
 
5.1%
i 496
 
4.5%
c 451
 
4.1%
h 426
 
3.9%
Other values (42) 4588
41.7%
Common
ValueCountFrequency (%)
2260
31.6%
. 673
 
9.4%
2 554
 
7.7%
1 532
 
7.4%
0 489
 
6.8%
) 486
 
6.8%
( 486
 
6.8%
3 330
 
4.6%
8 228
 
3.2%
4 226
 
3.2%
Other values (12) 891
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18166
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2260
 
12.4%
e 992
 
5.5%
o 961
 
5.3%
a 703
 
3.9%
. 673
 
3.7%
l 649
 
3.6%
r 595
 
3.3%
S 584
 
3.2%
n 566
 
3.1%
2 554
 
3.0%
Other values (64) 9629
53.0%

overview
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size439.7 KiB
2023-12-09T22:38:40.845320image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1807
Median length1016
Mean length892.1329114
Min length12

Characters and Unicode

Total characters422871
Distinct characters93
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st rowMock Trial; Restorative Practices; Student Centered Learning; MSQI
2nd rowPS/MS 140M is committed to creating a community of learners who have the opportunity to develop their character and intellect through project-based learning that encourages collaboration, inquiry and critical thinking. Learners will engage in real-world application of their understandings. We will be part of a respectful, inclusive learning environment, providing equity in our diverse learning community across all disciplines, making our students become leaders, change makers, active citizens and empowered members of our community. We have a quality Arts program which include dance, music/choral, and visual arts. M140 has many partnerships, such as Educational Alliance, Henry Street Mental Health Clinic, Rosie's Broadway Kids, Artist Space, Marquise Studios, Champs, ThriveNYC, NY Cares and Asphalt Green.
3rd rowShuang Wen has received honors including NYSED Recognition School (2018-19), U.S. Blue Ribbon School (since 2013), and NYS Reward School (since 2013). We have school-wide Chinese-English Dual Language Classes and ICT classes from K-8. We also have our After School Program, Monday-Friday, 2:40-5:00 p.m.
4th rowOur mission at the Island School is to be relentless in our pursuit of best practices to support student success. One way that we have done that and will continue to do it is by giving students a wide array of experiences so that they can identify areas of interest and talent and then develop those interests and talents into lifelong passions. Our faculty is committed to helping each of our children reach their full academic potential. We are developing a culture of college-minded students and working with community members to create a challenging learning environment. As a Community School, we look at how we can support the whole child. We provide services not only for our children but for our families. Parents like that we help identify and nurture their children's interest as well as their own talents. Parents appreciate our partnerships with high schools such as Bard High School Early College and Orchard Collegiate High School.
5th rowSomething that makes UNMS so special is the goal we share in providing a nurturing and valuable school experience for our children. We believe that education plays a crucial role in the successful academic, emotional, and physical development of every child. Our learning community inspires our students because we have an amazing group of educators who instill a passion for learning and a commitment to make a difference. UNMS is committed to work relentlessly to support a learning environment where each child is cared for, valued and seen. We are committed to providing opportunities that promote collaboration between our UNMS community members because we know it takes a village to teach the whole child. Together we make the difference!
ValueCountFrequency (%)
and 3356
 
5.3%
the 2116
 
3.3%
to 1964
 
3.1%
students 1501
 
2.4%
our 1497
 
2.3%
a 1473
 
2.3%
in 1398
 
2.2%
of 1329
 
2.1%
school 1258
 
2.0%
we 1007
 
1.6%
Other values (5389) 46817
73.5%
2023-12-09T22:38:41.449361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
64011
15.1%
e 39156
 
9.3%
t 28219
 
6.7%
a 26689
 
6.3%
o 25588
 
6.1%
n 24806
 
5.9%
i 24387
 
5.8%
r 23229
 
5.5%
s 22832
 
5.4%
l 16258
 
3.8%
Other values (83) 127696
30.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 331774
78.5%
Space Separator 64021
 
15.1%
Uppercase Letter 14065
 
3.3%
Other Punctuation 9277
 
2.2%
Decimal Number 2092
 
0.5%
Dash Punctuation 1073
 
0.3%
Close Punctuation 235
 
0.1%
Open Punctuation 234
 
0.1%
Control 87
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2185
15.5%
A 1418
 
10.1%
C 1028
 
7.3%
T 940
 
6.7%
W 886
 
6.3%
M 868
 
6.2%
P 793
 
5.6%
E 774
 
5.5%
O 622
 
4.4%
I 590
 
4.2%
Other values (18) 3961
28.2%
Lowercase Letter
ValueCountFrequency (%)
e 39156
11.8%
t 28219
 
8.5%
a 26689
 
8.0%
o 25588
 
7.7%
n 24806
 
7.5%
i 24387
 
7.4%
r 23229
 
7.0%
s 22832
 
6.9%
l 16258
 
4.9%
c 14552
 
4.4%
Other values (16) 86058
25.9%
Other Punctuation
ValueCountFrequency (%)
, 4550
49.0%
. 3569
38.5%
' 299
 
3.2%
: 188
 
2.0%
" 171
 
1.8%
/ 165
 
1.8%
; 135
 
1.5%
! 86
 
0.9%
& 69
 
0.7%
% 31
 
0.3%
Other values (4) 14
 
0.2%
Decimal Number
ValueCountFrequency (%)
1 398
19.0%
2 369
17.6%
0 270
12.9%
8 249
11.9%
3 183
8.7%
6 158
 
7.6%
7 125
 
6.0%
5 122
 
5.8%
9 118
 
5.6%
4 100
 
4.8%
Control
ValueCountFrequency (%)
‚ 42
48.3%
ƒ 25
28.7%
13
 
14.9%
” 4
 
4.6%
“ 2
 
2.3%
Â’ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
64011
> 99.9%
  10
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 232
98.7%
] 3
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 231
98.7%
[ 3
 
1.3%
Math Symbol
ValueCountFrequency (%)
> 7
53.8%
+ 6
46.2%
Dash Punctuation
ValueCountFrequency (%)
- 1073
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 345839
81.8%
Common 77032
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 39156
 
11.3%
t 28219
 
8.2%
a 26689
 
7.7%
o 25588
 
7.4%
n 24806
 
7.2%
i 24387
 
7.1%
r 23229
 
6.7%
s 22832
 
6.6%
l 16258
 
4.7%
c 14552
 
4.2%
Other values (44) 100123
29.0%
Common
ValueCountFrequency (%)
64011
83.1%
, 4550
 
5.9%
. 3569
 
4.6%
- 1073
 
1.4%
1 398
 
0.5%
2 369
 
0.5%
' 299
 
0.4%
0 270
 
0.4%
8 249
 
0.3%
) 232
 
0.3%
Other values (29) 2012
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 422703
> 99.9%
None 168
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
64011
15.1%
e 39156
 
9.3%
t 28219
 
6.7%
a 26689
 
6.3%
o 25588
 
6.1%
n 24806
 
5.9%
i 24387
 
5.8%
r 23229
 
5.5%
s 22832
 
5.4%
l 16258
 
3.8%
Other values (75) 127528
30.2%
None
ValueCountFrequency (%)
‚ 42
25.0%
à 42
25.0%
 42
25.0%
ƒ 25
14.9%
  10
 
6.0%
” 4
 
2.4%
“ 2
 
1.2%
Â’ 1
 
0.6%

neighborhood
Text

MISSING 

Distinct150
Distinct (%)32.3%
Missing9
Missing (%)1.9%
Memory size31.5 KiB
2023-12-09T22:38:41.769426image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length25
Median length17
Mean length11.39784946
Min length5

Characters and Unicode

Total characters5300
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)10.8%

Sample

1st rowEast Village
2nd rowLower East Side
3rd rowLower East Side
4th rowEast Village
5th rowLower East Side
ValueCountFrequency (%)
east 61
 
7.7%
heights 36
 
4.6%
park 29
 
3.7%
side 24
 
3.0%
harlem 22
 
2.8%
upper 18
 
2.3%
west 17
 
2.2%
south 17
 
2.2%
new 15
 
1.9%
york 15
 
1.9%
Other values (157) 535
67.8%
2023-12-09T22:38:42.244193image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 461
 
8.7%
a 412
 
7.8%
r 373
 
7.0%
o 341
 
6.4%
s 340
 
6.4%
t 335
 
6.3%
324
 
6.1%
i 291
 
5.5%
n 282
 
5.3%
l 252
 
4.8%
Other values (41) 1889
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4178
78.8%
Uppercase Letter 792
 
14.9%
Space Separator 324
 
6.1%
Dash Punctuation 4
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 461
11.0%
a 412
9.9%
r 373
 
8.9%
o 341
 
8.2%
s 340
 
8.1%
t 335
 
8.0%
i 291
 
7.0%
n 282
 
6.7%
l 252
 
6.0%
h 153
 
3.7%
Other values (14) 938
22.5%
Uppercase Letter
ValueCountFrequency (%)
H 105
13.3%
B 85
10.7%
S 72
 
9.1%
E 70
 
8.8%
C 47
 
5.9%
W 47
 
5.9%
P 44
 
5.6%
M 41
 
5.2%
F 41
 
5.2%
G 36
 
4.5%
Other values (14) 204
25.8%
Space Separator
ValueCountFrequency (%)
324
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4970
93.8%
Common 330
 
6.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 461
 
9.3%
a 412
 
8.3%
r 373
 
7.5%
o 341
 
6.9%
s 340
 
6.8%
t 335
 
6.7%
i 291
 
5.9%
n 282
 
5.7%
l 252
 
5.1%
h 153
 
3.1%
Other values (38) 1730
34.8%
Common
ValueCountFrequency (%)
324
98.2%
- 4
 
1.2%
. 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 461
 
8.7%
a 412
 
7.8%
r 373
 
7.0%
o 341
 
6.4%
s 340
 
6.4%
t 335
 
6.3%
324
 
6.1%
i 291
 
5.5%
n 282
 
5.3%
l 252
 
4.8%
Other values (41) 1889
35.6%

address
Text

Distinct414
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size43.4 KiB
2023-12-09T22:38:42.645991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length53
Median length43
Mean length36.58227848
Min length29

Characters and Unicode

Total characters17340
Distinct characters55
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique360 ?
Unique (%)75.9%

Sample

1st row730 EAST 12 STREET, MANHATTAN NY 10009
2nd row123 RIDGE STREET, MANHATTAN NY 10002
3rd row327 CHERRY STREET, MANHATTAN NY 10002
4th row442 EAST HOUSTON STREET, NEW YORK NY 10002
5th row220 HENRY STREET, MANHATTAN NY 10002
ValueCountFrequency (%)
ny 474
 
15.8%
street 207
 
6.9%
avenue 188
 
6.3%
brooklyn 143
 
4.8%
bronx 116
 
3.9%
queens 102
 
3.4%
manhattan 91
 
3.0%
east 56
 
1.9%
west 45
 
1.5%
road 21
 
0.7%
Other values (848) 1558
51.9%
2023-12-09T22:38:43.198859image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2527
14.6%
N 1407
 
8.1%
E 1407
 
8.1%
1 1264
 
7.3%
T 902
 
5.2%
A 817
 
4.7%
0 798
 
4.6%
R 716
 
4.1%
Y 675
 
3.9%
O 612
 
3.5%
Other values (45) 6215
35.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9731
56.1%
Decimal Number 4459
25.7%
Space Separator 2527
 
14.6%
Other Punctuation 476
 
2.7%
Dash Punctuation 101
 
0.6%
Lowercase Letter 46
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 1407
14.5%
E 1407
14.5%
T 902
9.3%
A 817
8.4%
R 716
 
7.4%
Y 675
 
6.9%
O 612
 
6.3%
S 563
 
5.8%
U 352
 
3.6%
B 343
 
3.5%
Other values (15) 1937
19.9%
Lowercase Letter
ValueCountFrequency (%)
t 8
17.4%
e 8
17.4%
r 5
10.9%
o 5
10.9%
n 4
8.7%
l 3
 
6.5%
k 3
 
6.5%
y 2
 
4.3%
h 1
 
2.2%
s 1
 
2.2%
Other values (6) 6
13.0%
Decimal Number
ValueCountFrequency (%)
1 1264
28.3%
0 798
17.9%
2 527
11.8%
4 388
 
8.7%
3 362
 
8.1%
5 350
 
7.8%
6 248
 
5.6%
7 216
 
4.8%
8 160
 
3.6%
9 146
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 474
99.6%
' 2
 
0.4%
Space Separator
ValueCountFrequency (%)
2527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9777
56.4%
Common 7563
43.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 1407
14.4%
E 1407
14.4%
T 902
9.2%
A 817
8.4%
R 716
 
7.3%
Y 675
 
6.9%
O 612
 
6.3%
S 563
 
5.8%
U 352
 
3.6%
B 343
 
3.5%
Other values (31) 1983
20.3%
Common
ValueCountFrequency (%)
2527
33.4%
1 1264
16.7%
0 798
 
10.6%
2 527
 
7.0%
, 474
 
6.3%
4 388
 
5.1%
3 362
 
4.8%
5 350
 
4.6%
6 248
 
3.3%
7 216
 
2.9%
Other values (4) 409
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17340
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2527
14.6%
N 1407
 
8.1%
E 1407
 
8.1%
1 1264
 
7.3%
T 902
 
5.2%
A 817
 
4.7%
0 798
 
4.6%
R 716
 
4.1%
Y 675
 
3.9%
O 612
 
3.5%
Other values (45) 6215
35.8%

sharedbuilding
Text

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-09T22:38:43.323166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters474
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row1
ValueCountFrequency (%)
1 257
54.2%
0 217
45.8%
2023-12-09T22:38:43.601405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 257
54.2%
0 217
45.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 474
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 257
54.2%
0 217
45.8%

Most occurring scripts

ValueCountFrequency (%)
Common 474
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 257
54.2%
0 217
45.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 257
54.2%
0 217
45.8%

accessibility
Text

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size34.2 KiB
2023-12-09T22:38:44.030643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length20
Median length16
Mean length16.52742616
Min length14

Characters and Unicode

Total characters7834
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNot Accessible
2nd rowNot Accessible
3rd rowPartially Accessible
4th rowFully Accessible
5th rowPartially Accessible
ValueCountFrequency (%)
accessible 474
50.0%
not 193
20.4%
partially 159
 
16.8%
fully 122
 
12.9%
2023-12-09T22:38:44.324639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 1036
13.2%
c 948
12.1%
e 948
12.1%
s 948
12.1%
i 633
8.1%
474
 
6.1%
A 474
 
6.1%
b 474
 
6.1%
t 352
 
4.5%
a 318
 
4.1%
Other values (7) 1229
15.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6412
81.8%
Uppercase Letter 948
 
12.1%
Space Separator 474
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 1036
16.2%
c 948
14.8%
e 948
14.8%
s 948
14.8%
i 633
9.9%
b 474
7.4%
t 352
 
5.5%
a 318
 
5.0%
y 281
 
4.4%
o 193
 
3.0%
Other values (2) 281
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
A 474
50.0%
N 193
20.4%
P 159
 
16.8%
F 122
 
12.9%
Space Separator
ValueCountFrequency (%)
474
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7360
93.9%
Common 474
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 1036
14.1%
c 948
12.9%
e 948
12.9%
s 948
12.9%
i 633
8.6%
A 474
6.4%
b 474
6.4%
t 352
 
4.8%
a 318
 
4.3%
y 281
 
3.8%
Other values (6) 948
12.9%
Common
ValueCountFrequency (%)
474
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 1036
13.2%
c 948
12.1%
e 948
12.1%
s 948
12.1%
i 633
8.1%
474
 
6.1%
A 474
 
6.1%
b 474
 
6.1%
t 352
 
4.5%
a 318
 
4.1%
Other values (7) 1229
15.7%

telephone
Text

Distinct473
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size32.0 KiB
2023-12-09T22:38:44.586550image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters5676
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique473 ?
Unique (%)100.0%

Sample

1st row212-228-4433
2nd row212-677-4680
3rd row212-602-9700
4th row212-677-5710
5th row212-267-5701
ValueCountFrequency (%)
718-369-7603 1
 
0.2%
718-339-4355 1
 
0.2%
718-977-6181 1
 
0.2%
718-639-3817 1
 
0.2%
718-246-6500 1
 
0.2%
212-544-8021 1
 
0.2%
212-254-1803 1
 
0.2%
718-495-7768 1
 
0.2%
212-678-2861 1
 
0.2%
718-620-9423 1
 
0.2%
Other values (463) 463
97.9%
2023-12-09T22:38:44.967986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 946
16.7%
1 715
12.6%
8 713
12.6%
7 669
11.8%
2 518
9.1%
0 451
7.9%
4 363
 
6.4%
6 362
 
6.4%
3 337
 
5.9%
5 324
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4730
83.3%
Dash Punctuation 946
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 715
15.1%
8 713
15.1%
7 669
14.1%
2 518
11.0%
0 451
9.5%
4 363
7.7%
6 362
7.7%
3 337
7.1%
5 324
6.8%
9 278
 
5.9%
Dash Punctuation
ValueCountFrequency (%)
- 946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 946
16.7%
1 715
12.6%
8 713
12.6%
7 669
11.8%
2 518
9.1%
0 451
7.9%
4 363
 
6.4%
6 362
 
6.4%
3 337
 
5.9%
5 324
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 946
16.7%
1 715
12.6%
8 713
12.6%
7 669
11.8%
2 518
9.1%
0 451
7.9%
4 363
 
6.4%
6 362
 
6.4%
3 337
 
5.9%
5 324
 
5.7%

independentwebsite
Text

MISSING 

Distinct270
Distinct (%)100.0%
Missing204
Missing (%)43.0%
Memory size26.4 KiB
2023-12-09T22:38:45.334840image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length67
Median length41
Mean length18.43703704
Min length10

Characters and Unicode

Total characters4978
Distinct characters62
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)100.0%

Sample

1st rowwww.psms34.org
2nd rowwww.ps184m.org
3rd rowwww.island188.org
4th rowwww.unmslearns.net/
5th rowwww.eschs.org
ValueCountFrequency (%)
www.bronxlgj.org 1
 
0.4%
www.pgms566.org 1
 
0.4%
www.ps83.org 1
 
0.4%
www.sites.google.com/ms356covo.org/covofamilysite 1
 
0.4%
www.22k381.wixsite.com/website 1
 
0.4%
www.psis30pta.org 1
 
0.4%
www.wscnyc.org 1
 
0.4%
www.ps89x.org 1
 
0.4%
www.is217.org 1
 
0.4%
www.28q217.org 1
 
0.4%
Other values (260) 260
96.3%
2023-12-09T22:38:45.871882image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 802
16.1%
. 550
 
11.0%
o 435
 
8.7%
s 291
 
5.8%
r 283
 
5.7%
g 222
 
4.5%
e 213
 
4.3%
m 202
 
4.1%
c 189
 
3.8%
a 159
 
3.2%
Other values (52) 1632
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3821
76.8%
Other Punctuation 591
 
11.9%
Decimal Number 453
 
9.1%
Uppercase Letter 106
 
2.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 802
21.0%
o 435
11.4%
s 291
 
7.6%
r 283
 
7.4%
g 222
 
5.8%
e 213
 
5.6%
m 202
 
5.3%
c 189
 
4.9%
a 159
 
4.2%
l 141
 
3.7%
Other values (16) 884
23.1%
Uppercase Letter
ValueCountFrequency (%)
S 27
25.5%
I 10
 
9.4%
M 10
 
9.4%
C 6
 
5.7%
A 6
 
5.7%
L 5
 
4.7%
P 5
 
4.7%
B 5
 
4.7%
E 4
 
3.8%
T 3
 
2.8%
Other values (12) 25
23.6%
Decimal Number
ValueCountFrequency (%)
1 87
19.2%
2 75
16.6%
3 56
12.4%
7 41
9.1%
4 40
8.8%
8 39
8.6%
9 33
 
7.3%
6 32
 
7.1%
0 27
 
6.0%
5 23
 
5.1%
Other Punctuation
ValueCountFrequency (%)
. 550
93.1%
/ 37
 
6.3%
: 4
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3927
78.9%
Common 1051
 
21.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 802
20.4%
o 435
11.1%
s 291
 
7.4%
r 283
 
7.2%
g 222
 
5.7%
e 213
 
5.4%
m 202
 
5.1%
c 189
 
4.8%
a 159
 
4.0%
l 141
 
3.6%
Other values (38) 990
25.2%
Common
ValueCountFrequency (%)
. 550
52.3%
1 87
 
8.3%
2 75
 
7.1%
3 56
 
5.3%
7 41
 
3.9%
4 40
 
3.8%
8 39
 
3.7%
/ 37
 
3.5%
9 33
 
3.1%
6 32
 
3.0%
Other values (4) 61
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 802
16.1%
. 550
 
11.0%
o 435
 
8.7%
s 291
 
5.8%
r 283
 
5.7%
g 222
 
4.5%
e 213
 
4.3%
m 202
 
4.1%
c 189
 
3.8%
a 159
 
3.2%
Other values (52) 1632
32.8%

subway
Text

MISSING 

Distinct264
Distinct (%)75.9%
Missing126
Missing (%)26.6%
Memory size36.6 KiB
2023-12-09T22:38:46.203795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length187
Median length87
Mean length38.54597701
Min length7

Characters and Unicode

Total characters13414
Distinct characters72
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)57.5%

Sample

1st rowL to 1st Ave
2nd rowF, J, M, Z to Delancey St-Essex St
3rd rowJ, M, Z to Delancey St-Essex St; F to East Broadway
4th rowJ, M, Z to Delancey St-Essex St; F to East Broadway; B, D to Grand St
5th rowF, J, M, Z to Delancey St-Essex St; B, D to Grand St
ValueCountFrequency (%)
to 606
 
18.7%
st 271
 
8.4%
ave 206
 
6.4%
b 89
 
2.7%
2 86
 
2.7%
79
 
2.4%
5 78
 
2.4%
d 75
 
2.3%
c 71
 
2.2%
a 69
 
2.1%
Other values (356) 1612
49.7%
2023-12-09T22:38:46.728112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2894
21.6%
t 1459
 
10.9%
o 922
 
6.9%
e 605
 
4.5%
, 482
 
3.6%
a 433
 
3.2%
S 397
 
3.0%
r 391
 
2.9%
h 327
 
2.4%
n 315
 
2.3%
Other values (62) 5189
38.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6312
47.1%
Space Separator 2894
21.6%
Uppercase Letter 2029
 
15.1%
Decimal Number 1181
 
8.8%
Other Punctuation 748
 
5.6%
Dash Punctuation 186
 
1.4%
Control 64
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 397
19.6%
A 312
15.4%
B 176
 
8.7%
C 152
 
7.5%
D 99
 
4.9%
F 86
 
4.2%
R 78
 
3.8%
M 76
 
3.7%
N 70
 
3.4%
P 67
 
3.3%
Other values (17) 516
25.4%
Lowercase Letter
ValueCountFrequency (%)
t 1459
23.1%
o 922
14.6%
e 605
9.6%
a 433
 
6.9%
r 391
 
6.2%
h 327
 
5.2%
n 315
 
5.0%
s 265
 
4.2%
v 257
 
4.1%
d 198
 
3.1%
Other values (15) 1140
18.1%
Decimal Number
ValueCountFrequency (%)
1 288
24.4%
2 156
13.2%
5 141
11.9%
3 131
11.1%
4 125
10.6%
6 122
10.3%
7 76
 
6.4%
8 53
 
4.5%
0 45
 
3.8%
9 44
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 482
64.4%
; 260
34.8%
& 3
 
0.4%
/ 2
 
0.3%
. 1
 
0.1%
Control
ValueCountFrequency (%)
‚ 32
50.0%
ƒ 31
48.4%
— 1
 
1.6%
Space Separator
ValueCountFrequency (%)
2894
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 186
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8341
62.2%
Common 5073
37.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1459
17.5%
o 922
 
11.1%
e 605
 
7.3%
a 433
 
5.2%
S 397
 
4.8%
r 391
 
4.7%
h 327
 
3.9%
n 315
 
3.8%
A 312
 
3.7%
s 265
 
3.2%
Other values (42) 2915
34.9%
Common
ValueCountFrequency (%)
2894
57.0%
, 482
 
9.5%
1 288
 
5.7%
; 260
 
5.1%
- 186
 
3.7%
2 156
 
3.1%
5 141
 
2.8%
3 131
 
2.6%
4 125
 
2.5%
6 122
 
2.4%
Other values (10) 288
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13286
99.0%
None 128
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2894
21.8%
t 1459
 
11.0%
o 922
 
6.9%
e 605
 
4.6%
, 482
 
3.6%
a 433
 
3.3%
S 397
 
3.0%
r 391
 
2.9%
h 327
 
2.5%
n 315
 
2.4%
Other values (57) 5061
38.1%
None
ValueCountFrequency (%)
 32
25.0%
à 32
25.0%
‚ 32
25.0%
ƒ 31
24.2%
— 1
 
0.8%

bus
Text

MISSING 

Distinct381
Distinct (%)81.9%
Missing9
Missing (%)1.9%
Memory size48.7 KiB
2023-12-09T22:38:47.258468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length255
Median length93
Mean length49.42795699
Min length2

Characters and Unicode

Total characters22984
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique308 ?
Unique (%)66.2%

Sample

1st rowM14A, M14D, M21, M23, M8, M9, X14, X2, X42, X5
2nd rowB39, M14A, M14D, M15, M15-SBS, M21, M22, M9
3rd rowM14A, M14D, M15, M15-SBS, M21, M22, M9, X14, X37, X38
4th rowM14A, M14D, M21, M22, M8, M9
5th rowB39, M14A, M14D, M15, M15-SBS, M21, M22, M9, X14, X37, X38
ValueCountFrequency (%)
bx15 58
 
1.3%
m101 54
 
1.2%
m3 51
 
1.2%
bx41 49
 
1.1%
bxm4 49
 
1.1%
bx2 47
 
1.1%
bx41-sbs 47
 
1.1%
bx1 45
 
1.0%
m5 45
 
1.0%
bx32 43
 
1.0%
Other values (319) 3915
88.9%
2023-12-09T22:38:47.981809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 3943
17.2%
3938
17.1%
B 2399
10.4%
1 1889
8.2%
M 1357
 
5.9%
x 1225
 
5.3%
4 1053
 
4.6%
2 995
 
4.3%
Q 893
 
3.9%
3 853
 
3.7%
Other values (13) 4439
19.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7992
34.8%
Uppercase Letter 5680
24.7%
Other Punctuation 3944
17.2%
Space Separator 3938
17.1%
Lowercase Letter 1225
 
5.3%
Dash Punctuation 205
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1889
23.6%
4 1053
13.2%
2 995
12.4%
3 853
10.7%
5 661
 
8.3%
6 654
 
8.2%
0 636
 
8.0%
7 465
 
5.8%
8 465
 
5.8%
9 321
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 2399
42.2%
M 1357
23.9%
Q 893
 
15.7%
S 521
 
9.2%
X 408
 
7.2%
A 77
 
1.4%
D 19
 
0.3%
J 6
 
0.1%
Other Punctuation
ValueCountFrequency (%)
, 3943
> 99.9%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3938
100.0%
Lowercase Letter
ValueCountFrequency (%)
x 1225
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16079
70.0%
Latin 6905
30.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 3943
24.5%
3938
24.5%
1 1889
11.7%
4 1053
 
6.5%
2 995
 
6.2%
3 853
 
5.3%
5 661
 
4.1%
6 654
 
4.1%
0 636
 
4.0%
7 465
 
2.9%
Other values (4) 992
 
6.2%
Latin
ValueCountFrequency (%)
B 2399
34.7%
M 1357
19.7%
x 1225
17.7%
Q 893
 
12.9%
S 521
 
7.5%
X 408
 
5.9%
A 77
 
1.1%
D 19
 
0.3%
J 6
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 3943
17.2%
3938
17.1%
B 2399
10.4%
1 1889
8.2%
M 1357
 
5.9%
x 1225
 
5.3%
4 1053
 
4.6%
2 995
 
4.3%
Q 893
 
3.9%
3 853
 
3.7%
Other values (13) 4439
19.3%

code_prog1
Text

UNIQUE 

Distinct474
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size28.8 KiB
2023-12-09T22:38:48.436750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.012658228
Min length5

Characters and Unicode

Total characters2376
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)100.0%

Sample

1st rowM034L
2nd rowM140S
3rd rowM184S
4th rowM188E
5th rowM332R
ValueCountFrequency (%)
x244l 1
 
0.2%
x301u 1
 
0.2%
k661l 1
 
0.2%
k363l 1
 
0.2%
q327l 1
 
0.2%
k691s 1
 
0.2%
q283l 1
 
0.2%
k354a 1
 
0.2%
m191s 1
 
0.2%
x206l 1
 
0.2%
Other values (464) 464
97.9%
2023-12-09T22:38:48.994487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 227
 
9.6%
1 193
 
8.1%
M 182
 
7.7%
3 171
 
7.2%
0 170
 
7.2%
K 143
 
6.0%
U 132
 
5.6%
4 129
 
5.4%
8 123
 
5.2%
X 117
 
4.9%
Other values (13) 789
33.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1422
59.8%
Uppercase Letter 954
40.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 182
19.1%
K 143
15.0%
U 132
13.8%
X 117
12.3%
Q 105
11.0%
L 74
7.8%
A 51
 
5.3%
S 48
 
5.0%
E 43
 
4.5%
Z 31
 
3.2%
Other values (3) 28
 
2.9%
Decimal Number
ValueCountFrequency (%)
2 227
16.0%
1 193
13.6%
3 171
12.0%
0 170
12.0%
4 129
9.1%
8 123
8.6%
6 111
7.8%
5 107
7.5%
7 96
6.8%
9 95
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1422
59.8%
Latin 954
40.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 182
19.1%
K 143
15.0%
U 132
13.8%
X 117
12.3%
Q 105
11.0%
L 74
7.8%
A 51
 
5.3%
S 48
 
5.0%
E 43
 
4.5%
Z 31
 
3.2%
Other values (3) 28
 
2.9%
Common
ValueCountFrequency (%)
2 227
16.0%
1 193
13.6%
3 171
12.0%
0 170
12.0%
4 129
9.1%
8 123
8.6%
6 111
7.8%
5 107
7.5%
7 96
6.8%
9 95
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 227
 
9.6%
1 193
 
8.1%
M 182
 
7.7%
3 171
 
7.2%
0 170
 
7.2%
K 143
 
6.0%
U 132
 
5.6%
4 129
 
5.4%
8 123
 
5.2%
X 117
 
4.9%
Other values (13) 789
33.2%

name_prog1
Text

Distinct456
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size43.0 KiB
2023-12-09T22:38:49.407875image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length86
Median length60
Mean length35.67932489
Min length4

Characters and Unicode

Total characters16912
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique447 ?
Unique (%)94.3%

Sample

1st rowFranklin Delano Roosevelt (P.S. 34)
2nd rowNathan Straus Preparatory School (P.S. 140)
3rd rowShuang Wen (P.S. 184) Chinese Dual Language Program
4th rowP.S. 188 The Island School D75 Inclusion Program
5th rowNext Generation Extended Learning @ NYU
ValueCountFrequency (%)
school 192
 
7.5%
program 132
 
5.2%
the 97
 
3.8%
academy 81
 
3.2%
for 62
 
2.4%
middle 53
 
2.1%
m.s 48
 
1.9%
i.s 47
 
1.8%
of 44
 
1.7%
d75 43
 
1.7%
Other values (819) 1758
68.8%
2023-12-09T22:38:49.976698image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2083
 
12.3%
o 1165
 
6.9%
e 1162
 
6.9%
a 938
 
5.5%
r 867
 
5.1%
n 802
 
4.7%
l 716
 
4.2%
S 613
 
3.6%
i 611
 
3.6%
. 557
 
3.3%
Other values (64) 7398
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10426
61.6%
Uppercase Letter 2706
 
16.0%
Space Separator 2083
 
12.3%
Other Punctuation 706
 
4.2%
Decimal Number 684
 
4.0%
Close Punctuation 145
 
0.9%
Open Punctuation 145
 
0.9%
Dash Punctuation 16
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1165
11.2%
e 1162
11.1%
a 938
 
9.0%
r 867
 
8.3%
n 802
 
7.7%
l 716
 
6.9%
i 611
 
5.9%
c 552
 
5.3%
t 522
 
5.0%
h 479
 
4.6%
Other values (16) 2612
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 613
22.7%
P 302
11.2%
M 248
9.2%
A 226
 
8.4%
I 189
 
7.0%
T 143
 
5.3%
C 127
 
4.7%
L 100
 
3.7%
E 99
 
3.7%
D 95
 
3.5%
Other values (16) 564
20.8%
Decimal Number
ValueCountFrequency (%)
1 118
17.3%
2 107
15.6%
7 86
12.6%
5 86
12.6%
8 61
8.9%
3 59
8.6%
9 47
 
6.9%
4 42
 
6.1%
0 41
 
6.0%
6 37
 
5.4%
Other Punctuation
ValueCountFrequency (%)
. 557
78.9%
/ 60
 
8.5%
: 28
 
4.0%
& 25
 
3.5%
, 19
 
2.7%
' 15
 
2.1%
@ 2
 
0.3%
Space Separator
ValueCountFrequency (%)
2083
100.0%
Close Punctuation
ValueCountFrequency (%)
) 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 145
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13132
77.6%
Common 3780
 
22.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1165
 
8.9%
e 1162
 
8.8%
a 938
 
7.1%
r 867
 
6.6%
n 802
 
6.1%
l 716
 
5.5%
S 613
 
4.7%
i 611
 
4.7%
c 552
 
4.2%
t 522
 
4.0%
Other values (42) 5184
39.5%
Common
ValueCountFrequency (%)
2083
55.1%
. 557
 
14.7%
) 145
 
3.8%
( 145
 
3.8%
1 118
 
3.1%
2 107
 
2.8%
7 86
 
2.3%
5 86
 
2.3%
8 61
 
1.6%
/ 60
 
1.6%
Other values (12) 332
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16912
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2083
 
12.3%
o 1165
 
6.9%
e 1162
 
6.9%
a 938
 
5.5%
r 867
 
5.1%
n 802
 
4.7%
l 716
 
4.2%
S 613
 
3.6%
i 611
 
3.6%
. 557
 
3.3%
Other values (64) 7398
43.7%

admissionsmethod_prog1
Text

Distinct9
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size32.3 KiB
2023-12-09T22:38:50.195989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length18
Mean length12.42616034
Min length4

Characters and Unicode

Total characters5890
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLimited Unscreened
2nd rowScreened
3rd rowScreened: Language
4th rowD75 Special Education Inclusive Services
5th rowScreened
ValueCountFrequency (%)
open 142
17.7%
screened 128
15.9%
limited 74
9.2%
unscreened 74
9.2%
composite 45
 
5.6%
score 45
 
5.6%
services 43
 
5.4%
inclusive 43
 
5.4%
education 43
 
5.4%
special 43
 
5.4%
Other values (7) 123
15.3%
2023-12-09T22:38:50.545155image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1154
19.6%
n 568
 
9.6%
c 419
 
7.1%
i 365
 
6.2%
d 350
 
5.9%
329
 
5.6%
r 300
 
5.1%
S 269
 
4.6%
p 230
 
3.9%
o 214
 
3.6%
Other values (23) 1692
28.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4610
78.3%
Uppercase Letter 833
 
14.1%
Space Separator 329
 
5.6%
Decimal Number 86
 
1.5%
Other Punctuation 32
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1154
25.0%
n 568
12.3%
c 419
 
9.1%
i 365
 
7.9%
d 350
 
7.6%
r 300
 
6.5%
p 230
 
5.0%
o 214
 
4.6%
s 211
 
4.6%
t 174
 
3.8%
Other values (6) 625
13.6%
Uppercase Letter
ValueCountFrequency (%)
S 269
32.3%
O 142
17.0%
L 101
 
12.1%
U 74
 
8.9%
C 50
 
6.0%
E 48
 
5.8%
D 48
 
5.8%
I 43
 
5.2%
Z 31
 
3.7%
T 12
 
1.4%
Other values (2) 15
 
1.8%
Decimal Number
ValueCountFrequency (%)
5 43
50.0%
7 43
50.0%
Other Punctuation
ValueCountFrequency (%)
: 27
84.4%
/ 5
 
15.6%
Space Separator
ValueCountFrequency (%)
329
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5443
92.4%
Common 447
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1154
21.2%
n 568
10.4%
c 419
 
7.7%
i 365
 
6.7%
d 350
 
6.4%
r 300
 
5.5%
S 269
 
4.9%
p 230
 
4.2%
o 214
 
3.9%
s 211
 
3.9%
Other values (18) 1363
25.0%
Common
ValueCountFrequency (%)
329
73.6%
5 43
 
9.6%
7 43
 
9.6%
: 27
 
6.0%
/ 5
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5890
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1154
19.6%
n 568
 
9.6%
c 419
 
7.1%
i 365
 
6.2%
d 350
 
5.9%
329
 
5.6%
r 300
 
5.1%
S 269
 
4.6%
p 230
 
3.9%
o 214
 
3.6%
Other values (23) 1692
28.7%

geapps_prog1
Text

MISSING 

Distinct319
Distinct (%)76.1%
Missing55
Missing (%)11.6%
Memory size26.3 KiB
2023-12-09T22:38:51.130525image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.887828162
Min length1

Characters and Unicode

Total characters1210
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique239 ?
Unique (%)57.0%

Sample

1st row55
2nd row101
3rd row252
4th row59
5th row127
ValueCountFrequency (%)
77 4
 
1.0%
138 4
 
1.0%
114 3
 
0.7%
55 3
 
0.7%
166 3
 
0.7%
110 3
 
0.7%
142 3
 
0.7%
89 3
 
0.7%
826 3
 
0.7%
52 3
 
0.7%
Other values (309) 387
92.4%
2023-12-09T22:38:51.818847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 215
17.8%
2 173
14.3%
3 146
12.1%
4 122
10.1%
5 108
8.9%
6 106
8.8%
7 98
8.1%
8 87
7.2%
0 78
 
6.4%
9 77
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1210
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 215
17.8%
2 173
14.3%
3 146
12.1%
4 122
10.1%
5 108
8.9%
6 106
8.8%
7 98
8.1%
8 87
7.2%
0 78
 
6.4%
9 77
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common 1210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 215
17.8%
2 173
14.3%
3 146
12.1%
4 122
10.1%
5 108
8.9%
6 106
8.8%
7 98
8.1%
8 87
7.2%
0 78
 
6.4%
9 77
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 215
17.8%
2 173
14.3%
3 146
12.1%
4 122
10.1%
5 108
8.9%
6 106
8.8%
7 98
8.1%
8 87
7.2%
0 78
 
6.4%
9 77
 
6.4%

swdapps_prog1
Text

MISSING 

Distinct148
Distinct (%)35.3%
Missing55
Missing (%)11.6%
Memory size26.0 KiB
2023-12-09T22:38:52.253756image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.126491647
Min length1

Characters and Unicode

Total characters891
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)12.4%

Sample

1st row42
2nd row73
3rd row48
4th row37
5th row73
ValueCountFrequency (%)
44 10
 
2.4%
37 9
 
2.1%
42 9
 
2.1%
64 9
 
2.1%
35 8
 
1.9%
20 7
 
1.7%
82 7
 
1.7%
47 7
 
1.7%
23 7
 
1.7%
25 7
 
1.7%
Other values (138) 339
80.9%
2023-12-09T22:38:52.834604image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 146
16.4%
2 113
12.7%
4 102
11.4%
5 92
10.3%
6 85
9.5%
3 83
9.3%
7 78
8.8%
0 68
7.6%
8 66
7.4%
9 58
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 891
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 146
16.4%
2 113
12.7%
4 102
11.4%
5 92
10.3%
6 85
9.5%
3 83
9.3%
7 78
8.8%
0 68
7.6%
8 66
7.4%
9 58
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 891
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 146
16.4%
2 113
12.7%
4 102
11.4%
5 92
10.3%
6 85
9.5%
3 83
9.3%
7 78
8.8%
0 68
7.6%
8 66
7.4%
9 58
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 891
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 146
16.4%
2 113
12.7%
4 102
11.4%
5 92
10.3%
6 85
9.5%
3 83
9.3%
7 78
8.8%
0 68
7.6%
8 66
7.4%
9 58
 
6.5%

geappsperseat_prog1
Text

MISSING 

Distinct32
Distinct (%)7.7%
Missing57
Missing (%)12.0%
Memory size25.6 KiB
2023-12-09T22:38:53.029300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.143884892
Min length1

Characters and Unicode

Total characters477
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)2.2%

Sample

1st row1
2nd row2
3rd row3
4th row3
5th row2
ValueCountFrequency (%)
2 80
19.2%
3 71
17.0%
1 60
14.4%
4 44
10.6%
5 28
 
6.7%
6 27
 
6.5%
7 25
 
6.0%
8 11
 
2.6%
11 10
 
2.4%
18 8
 
1.9%
Other values (22) 53
12.7%
2023-12-09T22:38:53.340360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 114
23.9%
2 93
19.5%
3 82
17.2%
4 50
10.5%
5 37
 
7.8%
6 32
 
6.7%
7 30
 
6.3%
8 20
 
4.2%
0 12
 
2.5%
9 7
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 477
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 114
23.9%
2 93
19.5%
3 82
17.2%
4 50
10.5%
5 37
 
7.8%
6 32
 
6.7%
7 30
 
6.3%
8 20
 
4.2%
0 12
 
2.5%
9 7
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Common 477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 114
23.9%
2 93
19.5%
3 82
17.2%
4 50
10.5%
5 37
 
7.8%
6 32
 
6.7%
7 30
 
6.3%
8 20
 
4.2%
0 12
 
2.5%
9 7
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 114
23.9%
2 93
19.5%
3 82
17.2%
4 50
10.5%
5 37
 
7.8%
6 32
 
6.7%
7 30
 
6.3%
8 20
 
4.2%
0 12
 
2.5%
9 7
 
1.5%

swdappsperseat_prog1
Text

MISSING 

Distinct26
Distinct (%)6.4%
Missing67
Missing (%)14.1%
Memory size25.3 KiB
2023-12-09T22:38:53.512608image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.083538084
Min length1

Characters and Unicode

Total characters441
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.7%

Sample

1st row4
2nd row4
3rd row3
4th row5
5th row5
ValueCountFrequency (%)
2 83
20.4%
3 70
17.2%
4 53
13.0%
1 46
11.3%
5 45
11.1%
6 31
 
7.6%
7 15
 
3.7%
8 15
 
3.7%
0 12
 
2.9%
11 7
 
1.7%
Other values (16) 30
 
7.4%
2023-12-09T22:38:53.809025image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 93
21.1%
1 81
18.4%
3 75
17.0%
4 57
12.9%
5 50
11.3%
6 32
 
7.3%
0 19
 
4.3%
7 16
 
3.6%
8 15
 
3.4%
9 3
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 441
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 93
21.1%
1 81
18.4%
3 75
17.0%
4 57
12.9%
5 50
11.3%
6 32
 
7.3%
0 19
 
4.3%
7 16
 
3.6%
8 15
 
3.4%
9 3
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 441
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 93
21.1%
1 81
18.4%
3 75
17.0%
4 57
12.9%
5 50
11.3%
6 32
 
7.3%
0 19
 
4.3%
7 16
 
3.6%
8 15
 
3.4%
9 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 441
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 93
21.1%
1 81
18.4%
3 75
17.0%
4 57
12.9%
5 50
11.3%
6 32
 
7.3%
0 19
 
4.3%
7 16
 
3.6%
8 15
 
3.4%
9 3
 
0.7%

swdseats_prog1
Text

MISSING 

Distinct59
Distinct (%)14.1%
Missing55
Missing (%)11.6%
Memory size25.9 KiB
2023-12-09T22:38:54.071023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length1.828162291
Min length1

Characters and Unicode

Total characters766
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)5.5%

Sample

1st row12
2nd row18
3rd row19
4th row8
5th row15
ValueCountFrequency (%)
12 29
 
6.9%
16 26
 
6.2%
6 24
 
5.7%
15 23
 
5.5%
18 23
 
5.5%
10 21
 
5.0%
19 21
 
5.0%
13 20
 
4.8%
14 18
 
4.3%
17 17
 
4.1%
Other values (49) 197
47.0%
2023-12-09T22:38:54.482732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 250
32.6%
2 134
17.5%
6 65
 
8.5%
3 59
 
7.7%
5 51
 
6.7%
0 50
 
6.5%
4 42
 
5.5%
8 41
 
5.4%
9 38
 
5.0%
7 36
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 766
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 250
32.6%
2 134
17.5%
6 65
 
8.5%
3 59
 
7.7%
5 51
 
6.7%
0 50
 
6.5%
4 42
 
5.5%
8 41
 
5.4%
9 38
 
5.0%
7 36
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Common 766
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 250
32.6%
2 134
17.5%
6 65
 
8.5%
3 59
 
7.7%
5 51
 
6.7%
0 50
 
6.5%
4 42
 
5.5%
8 41
 
5.4%
9 38
 
5.0%
7 36
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 766
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 250
32.6%
2 134
17.5%
6 65
 
8.5%
3 59
 
7.7%
5 51
 
6.7%
0 50
 
6.5%
4 42
 
5.5%
8 41
 
5.4%
9 38
 
5.0%
7 36
 
4.7%

geseats_prog1
Text

MISSING 

Distinct134
Distinct (%)32.0%
Missing55
Missing (%)11.6%
Memory size26.1 KiB
2023-12-09T22:38:54.880348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.195704057
Min length1

Characters and Unicode

Total characters920
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)12.4%

Sample

1st row58
2nd row47
3rd row74
4th row22
5th row75
ValueCountFrequency (%)
74 18
 
4.3%
24 16
 
3.8%
76 11
 
2.6%
50 10
 
2.4%
60 10
 
2.4%
47 10
 
2.4%
75 9
 
2.1%
72 9
 
2.1%
49 8
 
1.9%
25 8
 
1.9%
Other values (124) 310
74.0%
2023-12-09T22:38:55.745544image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 124
13.5%
7 116
12.6%
2 108
11.7%
4 105
11.4%
5 105
11.4%
0 86
9.3%
6 82
8.9%
8 74
8.0%
9 62
6.7%
3 58
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 124
13.5%
7 116
12.6%
2 108
11.7%
4 105
11.4%
5 105
11.4%
0 86
9.3%
6 82
8.9%
8 74
8.0%
9 62
6.7%
3 58
6.3%

Most occurring scripts

ValueCountFrequency (%)
Common 920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 124
13.5%
7 116
12.6%
2 108
11.7%
4 105
11.4%
5 105
11.4%
0 86
9.3%
6 82
8.9%
8 74
8.0%
9 62
6.7%
3 58
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 124
13.5%
7 116
12.6%
2 108
11.7%
4 105
11.4%
5 105
11.4%
0 86
9.3%
6 82
8.9%
8 74
8.0%
9 62
6.7%
3 58
6.3%

gefilled_prog1
Text

MISSING 

Distinct2
Distinct (%)0.5%
Missing50
Missing (%)10.5%
Memory size25.7 KiB
2023-12-09T22:38:55.866158image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters424
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
1 233
55.0%
0 191
45.0%
2023-12-09T22:38:56.077202image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 233
55.0%
0 191
45.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 424
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 233
55.0%
0 191
45.0%

Most occurring scripts

ValueCountFrequency (%)
Common 424
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 233
55.0%
0 191
45.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 233
55.0%
0 191
45.0%

swdfilled_prog1
Text

MISSING 

Distinct2
Distinct (%)0.5%
Missing50
Missing (%)10.5%
Memory size25.7 KiB
2023-12-09T22:38:56.190892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters424
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 263
62.0%
0 161
38.0%
2023-12-09T22:38:56.413241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 263
62.0%
0 161
38.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 424
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 263
62.0%
0 161
38.0%

Most occurring scripts

ValueCountFrequency (%)
Common 424
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 263
62.0%
0 161
38.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 263
62.0%
0 161
38.0%

eligibility_prog1
Text

Distinct67
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size55.2 KiB
2023-12-09T22:38:56.721486image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length208
Median length201
Mean length61.91350211
Min length31

Characters and Unicode

Total characters29347
Distinct characters56
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)4.9%

Sample

1st rowOpen to students and residents of District 1
2nd rowOpen to students and residents of District 1
3rd rowOpen to students and residents of Manhattan
4th rowOpen to students currently in or recommended for District 75 Special Education Inclusive Services. If you are not currently in or recommended for these services, please contact D75info@schools.nyc.gov.
5th rowOpen to students and residents of District 1
ValueCountFrequency (%)
students 482
 
9.9%
open 474
 
9.7%
to 474
 
9.7%
and 419
 
8.6%
residents 394
 
8.1%
of 381
 
7.8%
district 254
 
5.2%
the 143
 
2.9%
in 126
 
2.6%
bronx 109
 
2.2%
Other values (84) 1609
33.1%
2023-12-09T22:38:57.208160image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4391
15.0%
t 2958
10.1%
e 2951
10.1%
n 2694
9.2%
s 2505
 
8.5%
o 1791
 
6.1%
d 1586
 
5.4%
r 1518
 
5.2%
i 1457
 
5.0%
c 910
 
3.1%
Other values (46) 6586
22.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 22722
77.4%
Space Separator 4391
 
15.0%
Uppercase Letter 1277
 
4.4%
Decimal Number 609
 
2.1%
Other Punctuation 328
 
1.1%
Dash Punctuation 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2958
13.0%
e 2951
13.0%
n 2694
11.9%
s 2505
11.0%
o 1791
7.9%
d 1586
7.0%
r 1518
6.7%
i 1457
6.4%
c 910
 
4.0%
a 776
 
3.4%
Other values (14) 3576
15.7%
Uppercase Letter
ValueCountFrequency (%)
O 465
36.4%
D 309
24.2%
B 131
 
10.3%
S 105
 
8.2%
I 91
 
7.1%
E 55
 
4.3%
C 29
 
2.3%
A 25
 
2.0%
N 19
 
1.5%
Q 19
 
1.5%
Other values (3) 29
 
2.3%
Decimal Number
ValueCountFrequency (%)
5 142
23.3%
2 116
19.0%
7 103
16.9%
1 84
13.8%
3 46
 
7.6%
9 31
 
5.1%
6 28
 
4.6%
0 21
 
3.4%
4 20
 
3.3%
8 18
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 201
61.3%
, 65
 
19.8%
@ 48
 
14.6%
; 10
 
3.0%
& 4
 
1.2%
Space Separator
ValueCountFrequency (%)
4391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 23999
81.8%
Common 5348
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2958
12.3%
e 2951
12.3%
n 2694
11.2%
s 2505
10.4%
o 1791
 
7.5%
d 1586
 
6.6%
r 1518
 
6.3%
i 1457
 
6.1%
c 910
 
3.8%
a 776
 
3.2%
Other values (27) 4853
20.2%
Common
ValueCountFrequency (%)
4391
82.1%
. 201
 
3.8%
5 142
 
2.7%
2 116
 
2.2%
7 103
 
1.9%
1 84
 
1.6%
, 65
 
1.2%
@ 48
 
0.9%
3 46
 
0.9%
9 31
 
0.6%
Other values (9) 121
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4391
15.0%
t 2958
10.1%
e 2951
10.1%
n 2694
9.2%
s 2505
 
8.5%
o 1791
 
6.1%
d 1586
 
5.4%
r 1518
 
5.2%
i 1457
 
5.0%
c 910
 
3.1%
Other values (46) 6586
22.4%

priority1_prog1
Text

MISSING 

Distinct70
Distinct (%)24.3%
Missing186
Missing (%)39.2%
Memory size35.5 KiB
2023-12-09T22:38:57.464754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length121
Median length102
Mean length48.23611111
Min length31

Characters and Unicode

Total characters13892
Distinct characters50
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)15.6%

Sample

1st rowPriority to continuing students
2nd rowPriority to continuing students
3rd rowPriority to continuing students
4th rowPriority to District 1 students and residents who sign in at an event
5th rowPriority to continuing students
ValueCountFrequency (%)
to 295
 
12.9%
priority 286
 
12.5%
students 225
 
9.8%
residents 182
 
7.9%
and 125
 
5.5%
district 109
 
4.8%
continuing 96
 
4.2%
of 74
 
3.2%
the 73
 
3.2%
school 69
 
3.0%
Other values (90) 759
33.1%
2023-12-09T22:38:57.866168image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2005
14.4%
t 1780
12.8%
i 1379
9.9%
n 1191
8.6%
s 1057
7.6%
o 1048
7.5%
e 975
 
7.0%
r 894
 
6.4%
d 693
 
5.0%
u 326
 
2.3%
Other values (40) 2544
18.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11098
79.9%
Space Separator 2005
 
14.4%
Uppercase Letter 493
 
3.5%
Decimal Number 272
 
2.0%
Other Punctuation 24
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1780
16.0%
i 1379
12.4%
n 1191
10.7%
s 1057
9.5%
o 1048
9.4%
e 975
8.8%
r 894
8.1%
d 693
 
6.2%
u 326
 
2.9%
y 293
 
2.6%
Other values (11) 1462
13.2%
Uppercase Letter
ValueCountFrequency (%)
P 319
64.7%
D 111
 
22.5%
S 37
 
7.5%
T 6
 
1.2%
G 4
 
0.8%
R 3
 
0.6%
B 2
 
0.4%
C 2
 
0.4%
Q 2
 
0.4%
I 2
 
0.4%
Other values (4) 5
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 83
30.5%
2 44
16.2%
9 29
 
10.7%
3 25
 
9.2%
0 21
 
7.7%
7 18
 
6.6%
8 18
 
6.6%
5 18
 
6.6%
6 10
 
3.7%
4 6
 
2.2%
Other Punctuation
ValueCountFrequency (%)
, 17
70.8%
& 4
 
16.7%
. 2
 
8.3%
/ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
2005
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11591
83.4%
Common 2301
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1780
15.4%
i 1379
11.9%
n 1191
10.3%
s 1057
9.1%
o 1048
9.0%
e 975
8.4%
r 894
7.7%
d 693
 
6.0%
u 326
 
2.8%
P 319
 
2.8%
Other values (25) 1929
16.6%
Common
ValueCountFrequency (%)
2005
87.1%
1 83
 
3.6%
2 44
 
1.9%
9 29
 
1.3%
3 25
 
1.1%
0 21
 
0.9%
7 18
 
0.8%
8 18
 
0.8%
5 18
 
0.8%
, 17
 
0.7%
Other values (5) 23
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2005
14.4%
t 1780
12.8%
i 1379
9.9%
n 1191
8.6%
s 1057
7.6%
o 1048
7.5%
e 975
 
7.0%
r 894
 
6.4%
d 693
 
5.0%
u 326
 
2.3%
Other values (40) 2544
18.3%

priority2_prog1
Text

MISSING 

Distinct54
Distinct (%)18.8%
Missing186
Missing (%)39.2%
Memory size34.0 KiB
2023-12-09T22:38:58.129357image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length71
Median length65
Mean length42.60763889
Min length31

Characters and Unicode

Total characters12271
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)8.0%

Sample

1st rowThen to District 1 students and residents who sign in at an event
2nd rowThen to District 1 students and residents
3rd rowThen to District 1 students and residents
4th rowThen to District 1 students and residents
5th rowThen to New York City residents
ValueCountFrequency (%)
to 293
13.7%
then 287
13.4%
residents 282
13.2%
students 199
9.3%
and 199
9.3%
district 126
 
5.9%
of 85
 
4.0%
zone 78
 
3.7%
school 78
 
3.7%
the 78
 
3.7%
Other values (63) 429
20.1%
2023-12-09T22:38:58.541565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1846
15.0%
e 1423
11.6%
t 1405
11.4%
n 1225
10.0%
s 1188
9.7%
d 769
 
6.3%
o 722
 
5.9%
i 615
 
5.0%
r 529
 
4.3%
h 461
 
3.8%
Other values (36) 2088
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9635
78.5%
Space Separator 1846
 
15.0%
Uppercase Letter 541
 
4.4%
Decimal Number 246
 
2.0%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1423
14.8%
t 1405
14.6%
n 1225
12.7%
s 1188
12.3%
d 769
8.0%
o 722
7.5%
i 615
6.4%
r 529
 
5.5%
h 461
 
4.8%
a 283
 
2.9%
Other values (12) 1015
10.5%
Uppercase Letter
ValueCountFrequency (%)
T 287
53.0%
D 126
23.3%
B 60
 
11.1%
S 12
 
2.2%
C 11
 
2.0%
Y 10
 
1.8%
N 10
 
1.8%
P 10
 
1.8%
Q 6
 
1.1%
M 4
 
0.7%
Other values (2) 5
 
0.9%
Decimal Number
ValueCountFrequency (%)
1 63
25.6%
2 54
22.0%
9 33
13.4%
3 21
 
8.5%
0 19
 
7.7%
8 16
 
6.5%
5 13
 
5.3%
7 12
 
4.9%
6 11
 
4.5%
4 4
 
1.6%
Space Separator
ValueCountFrequency (%)
1846
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10176
82.9%
Common 2095
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1423
14.0%
t 1405
13.8%
n 1225
12.0%
s 1188
11.7%
d 769
7.6%
o 722
7.1%
i 615
 
6.0%
r 529
 
5.2%
h 461
 
4.5%
T 287
 
2.8%
Other values (24) 1552
15.3%
Common
ValueCountFrequency (%)
1846
88.1%
1 63
 
3.0%
2 54
 
2.6%
9 33
 
1.6%
3 21
 
1.0%
0 19
 
0.9%
8 16
 
0.8%
5 13
 
0.6%
7 12
 
0.6%
6 11
 
0.5%
Other values (2) 7
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12271
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1846
15.0%
e 1423
11.6%
t 1405
11.4%
n 1225
10.0%
s 1188
9.7%
d 769
 
6.3%
o 722
 
5.9%
i 615
 
5.0%
r 529
 
4.3%
h 461
 
3.8%
Other values (36) 2088
17.0%

priority3_prog1
Text

MISSING 

Distinct37
Distinct (%)31.1%
Missing355
Missing (%)74.9%
Memory size23.2 KiB
2023-12-09T22:38:58.756144image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length66
Median length65
Mean length45.89915966
Min length36

Characters and Unicode

Total characters5462
Distinct characters39
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)13.4%

Sample

1st rowThen to District 1 students and residents
2nd rowThen to Manhattan students and residents
3rd rowThen to District 2 students and residents
4th rowThen to District 2 students and residents
5th rowThen to residents of the elementary school zone
ValueCountFrequency (%)
then 119
12.1%
to 119
12.1%
students 118
12.0%
and 118
12.0%
residents 116
11.8%
district 68
 
6.9%
bronx 43
 
4.4%
who 33
 
3.4%
sign 33
 
3.4%
in 33
 
3.4%
Other values (34) 183
18.6%
2023-12-09T22:38:59.101304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
864
15.8%
t 679
12.4%
n 657
12.0%
s 574
10.5%
e 548
10.0%
d 352
6.4%
i 318
 
5.8%
r 229
 
4.2%
o 201
 
3.7%
a 191
 
3.5%
Other values (29) 849
15.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4247
77.8%
Space Separator 864
 
15.8%
Uppercase Letter 237
 
4.3%
Decimal Number 112
 
2.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 679
16.0%
n 657
15.5%
s 574
13.5%
e 548
12.9%
d 352
8.3%
i 318
7.5%
r 229
 
5.4%
o 201
 
4.7%
a 191
 
4.5%
h 156
 
3.7%
Other values (12) 342
8.1%
Decimal Number
ValueCountFrequency (%)
1 31
27.7%
2 19
17.0%
9 15
13.4%
5 10
 
8.9%
8 8
 
7.1%
4 8
 
7.1%
6 6
 
5.4%
7 6
 
5.4%
0 5
 
4.5%
3 4
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
T 119
50.2%
D 68
28.7%
B 44
 
18.6%
Q 4
 
1.7%
M 2
 
0.8%
Space Separator
ValueCountFrequency (%)
864
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4484
82.1%
Common 978
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 679
15.1%
n 657
14.7%
s 574
12.8%
e 548
12.2%
d 352
7.9%
i 318
7.1%
r 229
 
5.1%
o 201
 
4.5%
a 191
 
4.3%
h 156
 
3.5%
Other values (17) 579
12.9%
Common
ValueCountFrequency (%)
864
88.3%
1 31
 
3.2%
2 19
 
1.9%
9 15
 
1.5%
5 10
 
1.0%
8 8
 
0.8%
4 8
 
0.8%
6 6
 
0.6%
7 6
 
0.6%
0 5
 
0.5%
Other values (2) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5462
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
864
15.8%
t 679
12.4%
n 657
12.0%
s 574
10.5%
e 548
10.0%
d 352
6.4%
i 318
 
5.8%
r 229
 
4.2%
o 201
 
3.7%
a 191
 
3.5%
Other values (29) 849
15.5%

priority4_prog1
Text

MISSING 

Distinct14
Distinct (%)26.9%
Missing422
Missing (%)89.0%
Memory size18.3 KiB
2023-12-09T22:38:59.328958image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length64
Mean length40.88461538
Min length36

Characters and Unicode

Total characters2126
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)13.5%

Sample

1st rowThen to District 2 students and residents who sign in at an event
2nd rowThen to residents of the elementary school zone
3rd rowThen to residents of the elementary school zone
4th rowThen to residents of the elementary school zone
5th rowThen to Manhattan students and residents who sign in at an event
ValueCountFrequency (%)
then 52
14.3%
residents 52
14.3%
to 52
14.3%
students 47
12.9%
and 47
12.9%
bronx 27
7.4%
district 18
 
4.9%
9 6
 
1.6%
school 5
 
1.4%
zone 5
 
1.4%
Other values (19) 53
14.6%
2023-12-09T22:38:59.678429image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
312
14.7%
n 254
11.9%
t 254
11.9%
e 238
11.2%
s 226
10.6%
d 146
6.9%
o 103
 
4.8%
r 102
 
4.8%
i 96
 
4.5%
h 67
 
3.2%
Other values (24) 328
15.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1689
79.4%
Space Separator 312
 
14.7%
Uppercase Letter 99
 
4.7%
Decimal Number 26
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 254
15.0%
t 254
15.0%
e 238
14.1%
s 226
13.4%
d 146
8.6%
o 103
6.1%
r 102
6.0%
i 96
 
5.7%
h 67
 
4.0%
a 63
 
3.7%
Other values (11) 140
8.3%
Decimal Number
ValueCountFrequency (%)
9 9
34.6%
1 6
23.1%
8 5
19.2%
2 3
 
11.5%
3 1
 
3.8%
7 1
 
3.8%
6 1
 
3.8%
Uppercase Letter
ValueCountFrequency (%)
T 52
52.5%
B 27
27.3%
D 18
 
18.2%
M 1
 
1.0%
Q 1
 
1.0%
Space Separator
ValueCountFrequency (%)
312
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1788
84.1%
Common 338
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 254
14.2%
t 254
14.2%
e 238
13.3%
s 226
12.6%
d 146
8.2%
o 103
5.8%
r 102
5.7%
i 96
 
5.4%
h 67
 
3.7%
a 63
 
3.5%
Other values (16) 239
13.4%
Common
ValueCountFrequency (%)
312
92.3%
9 9
 
2.7%
1 6
 
1.8%
8 5
 
1.5%
2 3
 
0.9%
3 1
 
0.3%
7 1
 
0.3%
6 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2126
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
312
14.7%
n 254
11.9%
t 254
11.9%
e 238
11.2%
s 226
10.6%
d 146
6.9%
o 103
 
4.8%
r 102
 
4.8%
i 96
 
4.5%
h 67
 
3.2%
Other values (24) 328
15.4%

priority5_prog1
Text

MISSING 

Distinct8
Distinct (%)40.0%
Missing454
Missing (%)95.8%
Memory size16.4 KiB
2023-12-09T22:38:59.918446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length60
Mean length50.25
Min length36

Characters and Unicode

Total characters1005
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)20.0%

Sample

1st rowThen to District 2 students and residents
2nd rowThen to District 4 students and residents
3rd rowThen to District 4 students and residents
4th rowThen to District 5 students and residents
5th rowThen to residents of the elementary school zone
ValueCountFrequency (%)
then 20
10.6%
residents 20
10.6%
to 20
10.6%
students 19
10.1%
and 19
10.1%
bronx 12
 
6.4%
at 10
 
5.3%
an 10
 
5.3%
event 10
 
5.3%
in 10
 
5.3%
Other values (13) 38
20.2%
2023-12-09T22:39:00.266792image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168
16.7%
n 133
13.2%
t 112
11.1%
e 104
10.3%
s 95
9.5%
d 58
 
5.8%
i 52
 
5.2%
o 48
 
4.8%
r 40
 
4.0%
a 40
 
4.0%
Other values (20) 155
15.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 791
78.7%
Space Separator 168
 
16.7%
Uppercase Letter 39
 
3.9%
Decimal Number 7
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 133
16.8%
t 112
14.2%
e 104
13.1%
s 95
12.0%
d 58
7.3%
i 52
 
6.6%
o 48
 
6.1%
r 40
 
5.1%
a 40
 
5.1%
h 32
 
4.0%
Other values (12) 77
9.7%
Decimal Number
ValueCountFrequency (%)
4 3
42.9%
5 2
28.6%
1 1
 
14.3%
2 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
T 20
51.3%
B 13
33.3%
D 6
 
15.4%
Space Separator
ValueCountFrequency (%)
168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 830
82.6%
Common 175
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 133
16.0%
t 112
13.5%
e 104
12.5%
s 95
11.4%
d 58
7.0%
i 52
 
6.3%
o 48
 
5.8%
r 40
 
4.8%
a 40
 
4.8%
h 32
 
3.9%
Other values (15) 116
14.0%
Common
ValueCountFrequency (%)
168
96.0%
4 3
 
1.7%
5 2
 
1.1%
1 1
 
0.6%
2 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1005
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168
16.7%
n 133
13.2%
t 112
11.1%
e 104
10.3%
s 95
9.5%
d 58
 
5.8%
i 52
 
5.2%
o 48
 
4.8%
r 40
 
4.0%
a 40
 
4.0%
Other values (20) 155
15.4%

priority6_prog1
Text

MISSING 

Distinct5
Distinct (%)41.7%
Missing462
Missing (%)97.5%
Memory size15.8 KiB
2023-12-09T22:39:00.482601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length60
Median length42
Mean length45.66666667
Min length36

Characters and Unicode

Total characters548
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st rowThen to District 5 students and residents
2nd rowThen to Bronx students and residents
3rd rowThen to Bronx students and residents
4th rowThen to Bronx students and residents
5th rowThen to Bronx students and residents who sign in at an event
ValueCountFrequency (%)
then 12
12.1%
to 12
12.1%
students 12
12.1%
and 12
12.1%
residents 12
12.1%
bronx 8
8.1%
who 4
 
4.0%
sign 4
 
4.0%
in 4
 
4.0%
at 4
 
4.0%
Other values (6) 15
15.2%
2023-12-09T22:39:00.834674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
15.9%
n 73
13.3%
t 62
11.3%
e 56
10.2%
s 55
10.0%
d 36
6.6%
o 26
 
4.7%
i 26
 
4.7%
r 24
 
4.4%
a 20
 
3.6%
Other values (16) 83
15.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 432
78.8%
Space Separator 87
 
15.9%
Uppercase Letter 24
 
4.4%
Decimal Number 5
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 73
16.9%
t 62
14.4%
e 56
13.0%
s 55
12.7%
d 36
8.3%
o 26
 
6.0%
i 26
 
6.0%
r 24
 
5.6%
a 20
 
4.6%
h 16
 
3.7%
Other values (9) 38
8.8%
Uppercase Letter
ValueCountFrequency (%)
T 12
50.0%
B 9
37.5%
D 3
 
12.5%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
0 2
40.0%
5 1
20.0%
Space Separator
ValueCountFrequency (%)
87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 456
83.2%
Common 92
 
16.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 73
16.0%
t 62
13.6%
e 56
12.3%
s 55
12.1%
d 36
7.9%
o 26
 
5.7%
i 26
 
5.7%
r 24
 
5.3%
a 20
 
4.4%
h 16
 
3.5%
Other values (12) 62
13.6%
Common
ValueCountFrequency (%)
87
94.6%
1 2
 
2.2%
0 2
 
2.2%
5 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 548
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
15.9%
n 73
13.3%
t 62
11.3%
e 56
10.2%
s 55
10.0%
d 36
6.6%
o 26
 
4.7%
i 26
 
4.7%
r 24
 
4.4%
a 20
 
3.6%
Other values (16) 83
15.1%

priority7_prog1
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing471
Missing (%)99.4%
Memory size15.1 KiB
2023-12-09T22:39:01.042710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length60
Median length40
Mean length45.33333333
Min length36

Characters and Unicode

Total characters136
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowThen to Manhattan students and residents
2nd rowThen to Bronx students and residents
3rd rowThen to Bronx students and residents who sign in at an event
ValueCountFrequency (%)
then 3
12.5%
to 3
12.5%
students 3
12.5%
and 3
12.5%
residents 3
12.5%
bronx 2
8.3%
manhattan 1
 
4.2%
who 1
 
4.2%
sign 1
 
4.2%
in 1
 
4.2%
Other values (3) 3
12.5%
2023-12-09T22:39:01.374707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
15.4%
n 20
14.7%
t 16
11.8%
e 14
10.3%
s 13
9.6%
d 9
6.6%
a 8
 
5.9%
o 6
 
4.4%
i 5
 
3.7%
h 5
 
3.7%
Other values (9) 19
14.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 109
80.1%
Space Separator 21
 
15.4%
Uppercase Letter 6
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 20
18.3%
t 16
14.7%
e 14
12.8%
s 13
11.9%
d 9
8.3%
a 8
 
7.3%
o 6
 
5.5%
i 5
 
4.6%
h 5
 
4.6%
r 5
 
4.6%
Other values (5) 8
 
7.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
50.0%
B 2
33.3%
M 1
 
16.7%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 115
84.6%
Common 21
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 20
17.4%
t 16
13.9%
e 14
12.2%
s 13
11.3%
d 9
7.8%
a 8
 
7.0%
o 6
 
5.2%
i 5
 
4.3%
h 5
 
4.3%
r 5
 
4.3%
Other values (8) 14
12.2%
Common
ValueCountFrequency (%)
21
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 136
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
15.4%
n 20
14.7%
t 16
11.8%
e 14
10.3%
s 13
9.6%
d 9
6.6%
a 8
 
5.9%
o 6
 
4.4%
i 5
 
3.7%
h 5
 
3.7%
Other values (9) 19
14.0%

prefnote_prog1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog1
Text

MISSING 

Distinct14
Distinct (%)7.9%
Missing297
Missing (%)62.7%
Memory size26.4 KiB
2023-12-09T22:39:01.671764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length207
Median length117
Mean length41.11299435
Min length10

Characters and Unicode

Total characters7277
Distinct characters55
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)2.8%

Sample

1st row4th Grade New York State ELA and Math Exams
2nd row4th Grade New York State ELA and Math Exams
3rd rowAcademic and Personal Behavior Scores
4th rowAttendance and Punctuality
5th row4th Grade New York State ELA and Math Exams
ValueCountFrequency (%)
4th 130
9.3%
grade 130
9.3%
new 129
9.2%
state 129
9.2%
york 129
9.2%
ela 128
9.2%
and 106
 
7.6%
math 84
 
6.0%
exams 83
 
5.9%
exam 46
 
3.3%
Other values (52) 304
21.7%
2023-12-09T22:39:02.113002image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1221
16.8%
a 708
 
9.7%
e 600
 
8.2%
t 591
 
8.1%
r 366
 
5.0%
d 284
 
3.9%
E 267
 
3.7%
h 263
 
3.6%
o 236
 
3.2%
s 214
 
2.9%
Other values (45) 2527
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4370
60.1%
Uppercase Letter 1293
 
17.8%
Space Separator 1221
 
16.8%
Decimal Number 262
 
3.6%
Other Punctuation 123
 
1.7%
Dash Punctuation 6
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 708
16.2%
e 600
13.7%
t 591
13.5%
r 366
8.4%
d 284
 
6.5%
h 263
 
6.0%
o 236
 
5.4%
s 214
 
4.9%
n 192
 
4.4%
m 163
 
3.7%
Other values (13) 753
17.2%
Uppercase Letter
ValueCountFrequency (%)
E 267
20.6%
S 169
13.1%
A 161
12.5%
L 148
11.4%
G 130
10.1%
Y 129
10.0%
N 129
10.0%
M 85
 
6.6%
P 23
 
1.8%
B 22
 
1.7%
Other values (7) 30
 
2.3%
Decimal Number
ValueCountFrequency (%)
4 130
49.6%
2 65
24.8%
5 30
 
11.5%
0 15
 
5.7%
1 14
 
5.3%
7 8
 
3.1%
Other Punctuation
ValueCountFrequency (%)
% 45
36.6%
: 45
36.6%
. 30
24.4%
, 2
 
1.6%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
1221
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5663
77.8%
Common 1614
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 708
 
12.5%
e 600
 
10.6%
t 591
 
10.4%
r 366
 
6.5%
d 284
 
5.0%
E 267
 
4.7%
h 263
 
4.6%
o 236
 
4.2%
s 214
 
3.8%
n 192
 
3.4%
Other values (30) 1942
34.3%
Common
ValueCountFrequency (%)
1221
75.7%
4 130
 
8.1%
2 65
 
4.0%
% 45
 
2.8%
: 45
 
2.8%
5 30
 
1.9%
. 30
 
1.9%
0 15
 
0.9%
1 14
 
0.9%
7 8
 
0.5%
Other values (5) 11
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7277
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1221
16.8%
a 708
 
9.7%
e 600
 
8.2%
t 591
 
8.1%
r 366
 
5.0%
d 284
 
3.9%
E 267
 
3.7%
h 263
 
3.6%
o 236
 
3.2%
s 214
 
2.9%
Other values (45) 2527
34.7%

selectioncriteria2_prog1
Text

MISSING 

Distinct13
Distinct (%)8.1%
Missing313
Missing (%)66.0%
Memory size23.3 KiB
2023-12-09T22:39:02.368194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length41
Mean length28.0310559
Min length8

Characters and Unicode

Total characters4513
Distinct characters51
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)3.1%

Sample

1st rowAcademic and Personal Behavior Scores
2nd rowAttendance
3rd rowAttendance
4th rowAttendance at an Information Session, Open House or School Tour
5th rowAttendance
ValueCountFrequency (%)
and 56
 
7.9%
academic 53
 
7.5%
personal 53
 
7.5%
behavior 53
 
7.5%
scores 53
 
7.5%
attendance 53
 
7.5%
4th 45
 
6.4%
grade 45
 
6.4%
math 44
 
6.2%
exam 44
 
6.2%
Other values (27) 209
29.5%
2023-12-09T22:39:02.748641image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
547
 
12.1%
e 472
 
10.5%
a 466
 
10.3%
t 300
 
6.6%
r 254
 
5.6%
n 233
 
5.2%
o 217
 
4.8%
c 216
 
4.8%
d 208
 
4.6%
h 143
 
3.2%
Other values (41) 1457
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3120
69.1%
Uppercase Letter 565
 
12.5%
Space Separator 547
 
12.1%
Decimal Number 162
 
3.6%
Other Punctuation 118
 
2.6%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 472
15.1%
a 466
14.9%
t 300
9.6%
r 254
8.1%
n 233
7.5%
o 217
7.0%
c 216
6.9%
d 208
6.7%
h 143
 
4.6%
s 117
 
3.8%
Other values (12) 494
15.8%
Uppercase Letter
ValueCountFrequency (%)
A 107
18.9%
S 102
18.1%
P 56
9.9%
B 53
9.4%
E 46
8.1%
G 45
8.0%
M 44
7.8%
Y 44
7.8%
N 44
7.8%
L 10
 
1.8%
Other values (7) 14
 
2.5%
Decimal Number
ValueCountFrequency (%)
2 59
36.4%
4 45
27.8%
5 29
17.9%
0 15
 
9.3%
1 7
 
4.3%
7 7
 
4.3%
Other Punctuation
ValueCountFrequency (%)
% 44
37.3%
: 44
37.3%
. 29
24.6%
, 1
 
0.8%
Space Separator
ValueCountFrequency (%)
547
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3685
81.7%
Common 828
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 472
12.8%
a 466
12.6%
t 300
 
8.1%
r 254
 
6.9%
n 233
 
6.3%
o 217
 
5.9%
c 216
 
5.9%
d 208
 
5.6%
h 143
 
3.9%
s 117
 
3.2%
Other values (29) 1059
28.7%
Common
ValueCountFrequency (%)
547
66.1%
2 59
 
7.1%
4 45
 
5.4%
% 44
 
5.3%
: 44
 
5.3%
. 29
 
3.5%
5 29
 
3.5%
0 15
 
1.8%
1 7
 
0.8%
7 7
 
0.8%
Other values (2) 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
547
 
12.1%
e 472
 
10.5%
a 466
 
10.3%
t 300
 
6.6%
r 254
 
5.6%
n 233
 
5.2%
o 217
 
4.8%
c 216
 
4.8%
d 208
 
4.6%
h 143
 
3.2%
Other values (41) 1457
32.3%

selectioncriteria3_prog1
Text

MISSING 

Distinct20
Distinct (%)12.8%
Missing318
Missing (%)67.1%
Memory size21.6 KiB
2023-12-09T22:39:02.994465image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length54
Mean length19.05769231
Min length8

Characters and Unicode

Total characters2973
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)3.8%

Sample

1st rowAttendance
2nd rowELL Status
3rd rowLateness
4th rowDemonstrated Interest: School Visit or Written Contact
5th rowFinal 4th Grade Report Card
ValueCountFrequency (%)
attendance 73
16.9%
report 30
 
6.9%
card 30
 
6.9%
final 30
 
6.9%
grade 30
 
6.9%
4th 30
 
6.9%
and 24
 
5.5%
behaviors 23
 
5.3%
academic 23
 
5.3%
personal 23
 
5.3%
Other values (37) 117
27.0%
2023-12-09T22:39:03.409541image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 335
 
11.3%
a 291
 
9.8%
277
 
9.3%
n 271
 
9.1%
t 259
 
8.7%
d 182
 
6.1%
r 153
 
5.1%
c 124
 
4.2%
s 109
 
3.7%
A 103
 
3.5%
Other values (39) 869
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2156
72.5%
Uppercase Letter 346
 
11.6%
Space Separator 277
 
9.3%
Decimal Number 97
 
3.3%
Other Punctuation 92
 
3.1%
Dash Punctuation 5
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 335
15.5%
a 291
13.5%
n 271
12.6%
t 259
12.0%
d 182
8.4%
r 153
7.1%
c 124
 
5.8%
s 109
 
5.1%
o 102
 
4.7%
i 99
 
4.6%
Other values (10) 231
10.7%
Uppercase Letter
ValueCountFrequency (%)
A 103
29.8%
C 32
 
9.2%
R 30
 
8.7%
G 30
 
8.7%
F 30
 
8.7%
L 28
 
8.1%
P 25
 
7.2%
B 23
 
6.6%
S 16
 
4.6%
E 7
 
2.0%
Other values (7) 22
 
6.4%
Decimal Number
ValueCountFrequency (%)
4 30
30.9%
5 22
22.7%
0 21
21.6%
1 16
16.5%
2 7
 
7.2%
7 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 45
48.9%
% 44
47.8%
, 2
 
2.2%
/ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
277
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2502
84.2%
Common 471
 
15.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 335
13.4%
a 291
11.6%
n 271
10.8%
t 259
10.4%
d 182
 
7.3%
r 153
 
6.1%
c 124
 
5.0%
s 109
 
4.4%
A 103
 
4.1%
o 102
 
4.1%
Other values (27) 573
22.9%
Common
ValueCountFrequency (%)
277
58.8%
: 45
 
9.6%
% 44
 
9.3%
4 30
 
6.4%
5 22
 
4.7%
0 21
 
4.5%
1 16
 
3.4%
2 7
 
1.5%
- 5
 
1.1%
, 2
 
0.4%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2973
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 335
 
11.3%
a 291
 
9.8%
277
 
9.3%
n 271
 
9.1%
t 259
 
8.7%
d 182
 
6.1%
r 153
 
5.1%
c 124
 
4.2%
s 109
 
3.7%
A 103
 
3.5%
Other values (39) 869
29.2%

selectioncriteria4_prog1
Text

MISSING 

Distinct13
Distinct (%)9.4%
Missing336
Missing (%)70.9%
Memory size21.2 KiB
2023-12-09T22:39:03.643852image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length207
Median length29.5
Mean length21.52898551
Min length8

Characters and Unicode

Total characters2971
Distinct characters47
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)2.9%

Sample

1st rowOn-Site Assessment
2nd rowFinal 4th Grade Report Card
3rd rowFinal 4th Grade Report Card
4th rowOn-Site Assessment
5th rowLateness
ValueCountFrequency (%)
final 66
13.4%
grade 66
13.4%
report 66
13.4%
card 66
13.4%
4th 66
13.4%
lateness 26
 
5.3%
attendance 21
 
4.3%
45 17
 
3.4%
10 15
 
3.0%
assessment 13
 
2.6%
Other values (28) 72
14.6%
2023-12-09T22:39:04.033329image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
356
 
12.0%
e 291
 
9.8%
a 283
 
9.5%
t 255
 
8.6%
r 211
 
7.1%
n 179
 
6.0%
d 155
 
5.2%
s 120
 
4.0%
i 89
 
3.0%
4 88
 
3.0%
Other values (37) 944
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1961
66.0%
Uppercase Letter 401
 
13.5%
Space Separator 356
 
12.0%
Decimal Number 148
 
5.0%
Other Punctuation 90
 
3.0%
Dash Punctuation 13
 
0.4%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 291
14.8%
a 283
14.4%
t 255
13.0%
r 211
10.8%
n 179
9.1%
d 155
7.9%
s 120
6.1%
i 89
 
4.5%
l 77
 
3.9%
o 75
 
3.8%
Other values (11) 226
11.5%
Uppercase Letter
ValueCountFrequency (%)
C 66
16.5%
F 66
16.5%
R 66
16.5%
G 66
16.5%
L 50
12.5%
A 34
8.5%
S 21
 
5.2%
O 12
 
3.0%
E 12
 
3.0%
H 3
 
0.7%
Other values (5) 5
 
1.2%
Decimal Number
ValueCountFrequency (%)
4 88
59.5%
5 24
 
16.2%
0 21
 
14.2%
1 15
 
10.1%
Other Punctuation
ValueCountFrequency (%)
: 44
48.9%
% 44
48.9%
, 2
 
2.2%
Space Separator
ValueCountFrequency (%)
356
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2362
79.5%
Common 609
 
20.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 291
12.3%
a 283
12.0%
t 255
10.8%
r 211
 
8.9%
n 179
 
7.6%
d 155
 
6.6%
s 120
 
5.1%
i 89
 
3.8%
l 77
 
3.3%
o 75
 
3.2%
Other values (26) 627
26.5%
Common
ValueCountFrequency (%)
356
58.5%
4 88
 
14.4%
: 44
 
7.2%
% 44
 
7.2%
5 24
 
3.9%
0 21
 
3.4%
1 15
 
2.5%
- 13
 
2.1%
, 2
 
0.3%
) 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2971
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
356
 
12.0%
e 291
 
9.8%
a 283
 
9.5%
t 255
 
8.6%
r 211
 
7.1%
n 179
 
6.0%
d 155
 
5.2%
s 120
 
4.0%
i 89
 
3.0%
4 88
 
3.0%
Other values (37) 944
31.8%

selectioncriteria5_prog1
Text

MISSING 

Distinct10
Distinct (%)10.1%
Missing375
Missing (%)79.1%
Memory size19.0 KiB
2023-12-09T22:39:04.242563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length27
Mean length17.13131313
Min length8

Characters and Unicode

Total characters1696
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st rowHome Language
2nd rowLateness
3rd rowLateness
4th rowLateness
5th rowLateness
ValueCountFrequency (%)
lateness 37
13.9%
final 29
10.9%
4th 29
10.9%
grade 29
10.9%
report 29
10.9%
card 29
10.9%
punctuality 18
6.7%
5 15
5.6%
on-site 11
 
4.1%
assessment 11
 
4.1%
Other values (6) 30
11.2%
2023-12-09T22:39:04.569653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 173
 
10.2%
168
 
9.9%
t 153
 
9.0%
a 150
 
8.8%
s 118
 
7.0%
n 110
 
6.5%
r 87
 
5.1%
i 58
 
3.4%
d 58
 
3.4%
l 47
 
2.8%
Other values (25) 574
33.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1144
67.5%
Uppercase Letter 212
 
12.5%
Space Separator 168
 
9.9%
Decimal Number 87
 
5.1%
Other Punctuation 74
 
4.4%
Dash Punctuation 11
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 173
15.1%
t 153
13.4%
a 150
13.1%
s 118
10.3%
n 110
9.6%
r 87
7.6%
i 58
 
5.1%
d 58
 
5.1%
l 47
 
4.1%
u 40
 
3.5%
Other values (7) 150
13.1%
Uppercase Letter
ValueCountFrequency (%)
L 41
19.3%
R 29
13.7%
C 29
13.7%
F 29
13.7%
G 29
13.7%
P 18
8.5%
A 11
 
5.2%
S 11
 
5.2%
O 11
 
5.2%
H 4
 
1.9%
Decimal Number
ValueCountFrequency (%)
4 45
51.7%
5 27
31.0%
0 9
 
10.3%
3 6
 
6.9%
Other Punctuation
ValueCountFrequency (%)
: 37
50.0%
% 37
50.0%
Space Separator
ValueCountFrequency (%)
168
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1356
80.0%
Common 340
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 173
12.8%
t 153
11.3%
a 150
11.1%
s 118
 
8.7%
n 110
 
8.1%
r 87
 
6.4%
i 58
 
4.3%
d 58
 
4.3%
l 47
 
3.5%
L 41
 
3.0%
Other values (17) 361
26.6%
Common
ValueCountFrequency (%)
168
49.4%
4 45
 
13.2%
: 37
 
10.9%
% 37
 
10.9%
5 27
 
7.9%
- 11
 
3.2%
0 9
 
2.6%
3 6
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 173
 
10.2%
168
 
9.9%
t 153
 
9.0%
a 150
 
8.8%
s 118
 
7.0%
n 110
 
6.5%
r 87
 
5.1%
i 58
 
3.4%
d 58
 
3.4%
l 47
 
2.8%
Other values (25) 574
33.8%

selectioncriteria6_prog1
Text

MISSING 

Distinct5
Distinct (%)15.6%
Missing442
Missing (%)93.2%
Memory size16.2 KiB
2023-12-09T22:39:04.760105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length18
Mean length15.75
Min length8

Characters and Unicode

Total characters504
Distinct characters28
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)6.2%

Sample

1st rowLateness
2nd rowOn-Site Assessment
3rd rowOn-Site Assessment
4th rowOn-Site Assessment
5th rowOn-Site Assessment
ValueCountFrequency (%)
on-site 20
33.3%
assessment 20
33.3%
home 6
 
10.0%
language 6
 
10.0%
lateness 4
 
6.7%
spanish 1
 
1.7%
proficiency 1
 
1.7%
punctuality 1
 
1.7%
5 1
 
1.7%
2023-12-09T22:39:05.073143image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 89
17.7%
e 81
16.1%
n 53
10.5%
t 46
9.1%
28
 
5.6%
m 26
 
5.2%
i 24
 
4.8%
S 21
 
4.2%
O 20
 
4.0%
- 20
 
4.0%
Other values (18) 96
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 374
74.2%
Uppercase Letter 79
 
15.7%
Space Separator 28
 
5.6%
Dash Punctuation 20
 
4.0%
Other Punctuation 2
 
0.4%
Decimal Number 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 89
23.8%
e 81
21.7%
n 53
14.2%
t 46
12.3%
m 26
 
7.0%
i 24
 
6.4%
a 18
 
4.8%
g 12
 
3.2%
u 8
 
2.1%
o 7
 
1.9%
Other values (7) 10
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
S 21
26.6%
O 20
25.3%
A 20
25.3%
L 10
12.7%
H 6
 
7.6%
P 2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 453
89.9%
Common 51
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 89
19.6%
e 81
17.9%
n 53
11.7%
t 46
10.2%
m 26
 
5.7%
i 24
 
5.3%
S 21
 
4.6%
O 20
 
4.4%
A 20
 
4.4%
a 18
 
4.0%
Other values (13) 55
12.1%
Common
ValueCountFrequency (%)
28
54.9%
- 20
39.2%
: 1
 
2.0%
5 1
 
2.0%
% 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 504
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 89
17.7%
e 81
16.1%
n 53
10.5%
t 46
9.1%
28
 
5.6%
m 26
 
5.2%
i 24
 
4.8%
S 21
 
4.2%
O 20
 
4.0%
- 20
 
4.0%
Other values (18) 96
19.0%

selectioncriteria7_prog1
Text

MISSING 

Distinct2
Distinct (%)25.0%
Missing466
Missing (%)98.3%
Memory size15.2 KiB
2023-12-09T22:39:05.245628image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length10.5
Min length8

Characters and Unicode

Total characters84
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOn-Site Assessment
2nd rowLateness
3rd rowLateness
4th rowLateness
5th rowLateness
ValueCountFrequency (%)
lateness 6
60.0%
on-site 2
 
20.0%
assessment 2
 
20.0%
2023-12-09T22:39:05.538878image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 20
23.8%
e 18
21.4%
t 10
11.9%
n 10
11.9%
L 6
 
7.1%
a 6
 
7.1%
O 2
 
2.4%
- 2
 
2.4%
S 2
 
2.4%
i 2
 
2.4%
Other values (3) 6
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 68
81.0%
Uppercase Letter 12
 
14.3%
Dash Punctuation 2
 
2.4%
Space Separator 2
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 20
29.4%
e 18
26.5%
t 10
14.7%
n 10
14.7%
a 6
 
8.8%
i 2
 
2.9%
m 2
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
L 6
50.0%
O 2
 
16.7%
S 2
 
16.7%
A 2
 
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 80
95.2%
Common 4
 
4.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 20
25.0%
e 18
22.5%
t 10
12.5%
n 10
12.5%
L 6
 
7.5%
a 6
 
7.5%
O 2
 
2.5%
S 2
 
2.5%
i 2
 
2.5%
A 2
 
2.5%
Common
ValueCountFrequency (%)
- 2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 20
23.8%
e 18
21.4%
t 10
11.9%
n 10
11.9%
L 6
 
7.1%
a 6
 
7.1%
O 2
 
2.4%
- 2
 
2.4%
S 2
 
2.4%
i 2
 
2.4%
Other values (3) 6
 
7.1%

selectioncriteria8_prog1
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:39:06.098387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters36
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOn-Site Assessment
2nd rowOn-Site Assessment
ValueCountFrequency (%)
on-site 2
50.0%
assessment 2
50.0%
2023-12-09T22:39:06.402478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 8
22.2%
e 6
16.7%
n 4
11.1%
t 4
11.1%
O 2
 
5.6%
- 2
 
5.6%
S 2
 
5.6%
i 2
 
5.6%
2
 
5.6%
A 2
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 26
72.2%
Uppercase Letter 6
 
16.7%
Dash Punctuation 2
 
5.6%
Space Separator 2
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 8
30.8%
e 6
23.1%
n 4
15.4%
t 4
15.4%
i 2
 
7.7%
m 2
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
S 2
33.3%
A 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
88.9%
Common 4
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 8
25.0%
e 6
18.8%
n 4
12.5%
t 4
12.5%
O 2
 
6.2%
S 2
 
6.2%
i 2
 
6.2%
A 2
 
6.2%
m 2
 
6.2%
Common
ValueCountFrequency (%)
- 2
50.0%
2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 8
22.2%
e 6
16.7%
n 4
11.1%
t 4
11.1%
O 2
 
5.6%
- 2
 
5.6%
S 2
 
5.6%
i 2
 
5.6%
2
 
5.6%
A 2
 
5.6%

code_prog2
Text

MISSING 

Distinct175
Distinct (%)100.0%
Missing299
Missing (%)63.1%
Memory size20.1 KiB
2023-12-09T22:39:06.837690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.034285714
Min length5

Characters and Unicode

Total characters881
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)100.0%

Sample

1st rowM188S
2nd rowM332S
3rd rowM378M
4th rowM104N
5th rowM131N
ValueCountFrequency (%)
r002z 1
 
0.6%
q010z 1
 
0.6%
m514y 1
 
0.6%
q281y 1
 
0.6%
k763y 1
 
0.6%
x101e 1
 
0.6%
m177s 1
 
0.6%
m397l 1
 
0.6%
r075e 1
 
0.6%
x144v 1
 
0.6%
Other values (165) 165
94.3%
2023-12-09T22:39:07.403732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 89
 
10.1%
1 77
 
8.7%
0 75
 
8.5%
K 67
 
7.6%
3 52
 
5.9%
U 50
 
5.7%
4 47
 
5.3%
M 45
 
5.1%
8 42
 
4.8%
Z 41
 
4.7%
Other values (17) 296
33.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 525
59.6%
Uppercase Letter 356
40.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 67
18.8%
U 50
14.0%
M 45
12.6%
Z 41
11.5%
X 37
10.4%
Q 36
10.1%
Y 20
 
5.6%
R 12
 
3.4%
S 12
 
3.4%
L 11
 
3.1%
Other values (7) 25
 
7.0%
Decimal Number
ValueCountFrequency (%)
2 89
17.0%
1 77
14.7%
0 75
14.3%
3 52
9.9%
4 47
9.0%
8 42
8.0%
7 40
7.6%
6 40
7.6%
9 39
7.4%
5 24
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
Common 525
59.6%
Latin 356
40.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 67
18.8%
U 50
14.0%
M 45
12.6%
Z 41
11.5%
X 37
10.4%
Q 36
10.1%
Y 20
 
5.6%
R 12
 
3.4%
S 12
 
3.4%
L 11
 
3.1%
Other values (7) 25
 
7.0%
Common
ValueCountFrequency (%)
2 89
17.0%
1 77
14.7%
0 75
14.3%
3 52
9.9%
4 47
9.0%
8 42
8.0%
7 40
7.6%
6 40
7.6%
9 39
7.4%
5 24
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 881
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 89
 
10.1%
1 77
 
8.7%
0 75
 
8.5%
K 67
 
7.6%
3 52
 
5.9%
U 50
 
5.7%
4 47
 
5.3%
M 45
 
5.1%
8 42
 
4.8%
Z 41
 
4.7%
Other values (17) 296
33.6%

name_prog2
Text

MISSING 

Distinct151
Distinct (%)86.3%
Missing299
Missing (%)63.1%
Memory size24.9 KiB
2023-12-09T22:39:07.860332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length79
Median length54
Mean length33.41142857
Min length5

Characters and Unicode

Total characters5847
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique146 ?
Unique (%)83.4%

Sample

1st rowThe Island School (P.S. 188)
2nd rowUniversity Neighborhood Middle School
3rd rowSchool for Global Leaders Mandarin Dual Language Program
4th rowSpecial Progress
5th rowSpecial Progress
ValueCountFrequency (%)
program 82
 
9.1%
school 50
 
5.6%
the 32
 
3.6%
zoned 28
 
3.1%
i.s 22
 
2.4%
academy 21
 
2.3%
asd 19
 
2.1%
dual 16
 
1.8%
language 16
 
1.8%
of 16
 
1.8%
Other values (352) 597
66.4%
2023-12-09T22:39:08.503296image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
725
 
12.4%
e 325
 
5.6%
o 322
 
5.5%
a 309
 
5.3%
r 289
 
4.9%
S 250
 
4.3%
n 222
 
3.8%
. 188
 
3.2%
i 164
 
2.8%
l 160
 
2.7%
Other values (61) 2893
49.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2987
51.1%
Uppercase Letter 1572
26.9%
Space Separator 725
 
12.4%
Other Punctuation 243
 
4.2%
Decimal Number 223
 
3.8%
Open Punctuation 48
 
0.8%
Close Punctuation 48
 
0.8%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 250
15.9%
A 136
 
8.7%
P 134
 
8.5%
M 105
 
6.7%
O 94
 
6.0%
R 90
 
5.7%
E 89
 
5.7%
I 83
 
5.3%
T 79
 
5.0%
L 74
 
4.7%
Other values (16) 438
27.9%
Lowercase Letter
ValueCountFrequency (%)
e 325
10.9%
o 322
10.8%
a 309
 
10.3%
r 289
 
9.7%
n 222
 
7.4%
i 164
 
5.5%
l 160
 
5.4%
t 152
 
5.1%
g 135
 
4.5%
h 133
 
4.5%
Other values (15) 776
26.0%
Decimal Number
ValueCountFrequency (%)
2 43
19.3%
1 40
17.9%
8 21
9.4%
9 19
8.5%
6 18
8.1%
5 17
 
7.6%
7 17
 
7.6%
3 17
 
7.6%
4 16
 
7.2%
0 15
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 188
77.4%
/ 18
 
7.4%
: 17
 
7.0%
& 12
 
4.9%
, 7
 
2.9%
' 1
 
0.4%
Space Separator
ValueCountFrequency (%)
725
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4559
78.0%
Common 1288
 
22.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 325
 
7.1%
o 322
 
7.1%
a 309
 
6.8%
r 289
 
6.3%
S 250
 
5.5%
n 222
 
4.9%
i 164
 
3.6%
l 160
 
3.5%
t 152
 
3.3%
A 136
 
3.0%
Other values (41) 2230
48.9%
Common
ValueCountFrequency (%)
725
56.3%
. 188
 
14.6%
( 48
 
3.7%
) 48
 
3.7%
2 43
 
3.3%
1 40
 
3.1%
8 21
 
1.6%
9 19
 
1.5%
/ 18
 
1.4%
6 18
 
1.4%
Other values (10) 120
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5847
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
725
 
12.4%
e 325
 
5.6%
o 322
 
5.5%
a 309
 
5.3%
r 289
 
4.9%
S 250
 
4.3%
n 222
 
3.8%
. 188
 
3.2%
i 164
 
2.8%
l 160
 
2.7%
Other values (61) 2893
49.5%

admissionsmethod_prog2
Text

MISSING 

Distinct9
Distinct (%)5.1%
Missing299
Missing (%)63.1%
Memory size20.8 KiB
2023-12-09T22:39:08.707230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length18
Mean length9.337142857
Min length4

Characters and Unicode

Total characters1634
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowScreened
2nd rowScreened
3rd rowScreened: Language
4th rowScreened
5th rowScreened
ValueCountFrequency (%)
open 55
22.4%
zoned 41
16.7%
screened 34
13.9%
asd/aces 23
9.4%
program 23
9.4%
language 13
 
5.3%
limited 11
 
4.5%
unscreened 11
 
4.5%
test 6
 
2.4%
talent 6
 
2.4%
Other values (7) 22
 
9.0%
2023-12-09T22:39:09.032775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 285
17.4%
n 179
 
11.0%
d 101
 
6.2%
r 96
 
5.9%
S 89
 
5.4%
o 71
 
4.3%
70
 
4.3%
a 63
 
3.9%
c 62
 
3.8%
p 60
 
3.7%
Other values (23) 558
34.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1137
69.6%
Uppercase Letter 383
 
23.4%
Space Separator 70
 
4.3%
Other Punctuation 36
 
2.2%
Decimal Number 8
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 285
25.1%
n 179
15.7%
d 101
 
8.9%
r 96
 
8.4%
o 71
 
6.2%
a 63
 
5.5%
c 62
 
5.5%
p 60
 
5.3%
g 49
 
4.3%
i 39
 
3.4%
Other values (6) 132
11.6%
Uppercase Letter
ValueCountFrequency (%)
S 89
23.2%
O 55
14.4%
A 46
12.0%
Z 41
10.7%
E 27
 
7.0%
D 27
 
7.0%
L 24
 
6.3%
C 24
 
6.3%
P 23
 
6.0%
T 12
 
3.1%
Other values (2) 15
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/ 23
63.9%
: 13
36.1%
Decimal Number
ValueCountFrequency (%)
7 4
50.0%
5 4
50.0%
Space Separator
ValueCountFrequency (%)
70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1520
93.0%
Common 114
 
7.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 285
18.8%
n 179
 
11.8%
d 101
 
6.6%
r 96
 
6.3%
S 89
 
5.9%
o 71
 
4.7%
a 63
 
4.1%
c 62
 
4.1%
p 60
 
3.9%
O 55
 
3.6%
Other values (18) 459
30.2%
Common
ValueCountFrequency (%)
70
61.4%
/ 23
 
20.2%
: 13
 
11.4%
7 4
 
3.5%
5 4
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1634
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 285
17.4%
n 179
 
11.0%
d 101
 
6.2%
r 96
 
5.9%
S 89
 
5.4%
o 71
 
4.3%
70
 
4.3%
a 63
 
3.9%
c 62
 
3.8%
p 60
 
3.7%
Other values (23) 558
34.1%

geapps_prog2
Text

MISSING 

Distinct125
Distinct (%)86.8%
Missing330
Missing (%)69.6%
Memory size18.9 KiB
2023-12-09T22:39:09.420935image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.826388889
Min length1

Characters and Unicode

Total characters407
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)75.0%

Sample

1st row77
2nd row133
3rd row48
4th row825
5th row173
ValueCountFrequency (%)
152 3
 
2.1%
133 3
 
2.1%
125 2
 
1.4%
119 2
 
1.4%
42 2
 
1.4%
222 2
 
1.4%
105 2
 
1.4%
106 2
 
1.4%
48 2
 
1.4%
276 2
 
1.4%
Other values (115) 122
84.7%
2023-12-09T22:39:09.935203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 73
17.9%
2 65
16.0%
3 60
14.7%
5 39
9.6%
7 34
8.4%
4 32
7.9%
8 30
7.4%
6 30
7.4%
9 24
 
5.9%
0 20
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 407
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 73
17.9%
2 65
16.0%
3 60
14.7%
5 39
9.6%
7 34
8.4%
4 32
7.9%
8 30
7.4%
6 30
7.4%
9 24
 
5.9%
0 20
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 407
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 73
17.9%
2 65
16.0%
3 60
14.7%
5 39
9.6%
7 34
8.4%
4 32
7.9%
8 30
7.4%
6 30
7.4%
9 24
 
5.9%
0 20
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 407
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 73
17.9%
2 65
16.0%
3 60
14.7%
5 39
9.6%
7 34
8.4%
4 32
7.9%
8 30
7.4%
6 30
7.4%
9 24
 
5.9%
0 20
 
4.9%

swdapps_prog2
Text

MISSING 

Distinct83
Distinct (%)57.6%
Missing330
Missing (%)69.6%
Memory size18.7 KiB
2023-12-09T22:39:10.273279image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.013888889
Min length1

Characters and Unicode

Total characters290
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)31.2%

Sample

1st row40
2nd row76
3rd row18
4th row51
5th row10
ValueCountFrequency (%)
51 5
 
3.5%
14 5
 
3.5%
40 4
 
2.8%
10 4
 
2.8%
29 4
 
2.8%
33 3
 
2.1%
84 3
 
2.1%
15 3
 
2.1%
5 3
 
2.1%
17 3
 
2.1%
Other values (73) 107
74.3%
2023-12-09T22:39:10.763738image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 50
17.2%
5 33
11.4%
4 33
11.4%
2 31
10.7%
3 31
10.7%
7 28
9.7%
8 25
8.6%
6 24
8.3%
0 21
7.2%
9 14
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 290
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 50
17.2%
5 33
11.4%
4 33
11.4%
2 31
10.7%
3 31
10.7%
7 28
9.7%
8 25
8.6%
6 24
8.3%
0 21
7.2%
9 14
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 290
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 50
17.2%
5 33
11.4%
4 33
11.4%
2 31
10.7%
3 31
10.7%
7 28
9.7%
8 25
8.6%
6 24
8.3%
0 21
7.2%
9 14
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 50
17.2%
5 33
11.4%
4 33
11.4%
2 31
10.7%
3 31
10.7%
7 28
9.7%
8 25
8.6%
6 24
8.3%
0 21
7.2%
9 14
 
4.8%

geappsperseat_prog2
Text

MISSING 

Distinct20
Distinct (%)14.0%
Missing331
Missing (%)69.8%
Memory size18.6 KiB
2023-12-09T22:39:10.925270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.083916084
Min length1

Characters and Unicode

Total characters155
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)6.3%

Sample

1st row2
2nd row2
3rd row2
4th row4
5th row4
ValueCountFrequency (%)
1 34
23.8%
2 34
23.8%
3 22
15.4%
4 13
 
9.1%
5 9
 
6.3%
6 7
 
4.9%
0 4
 
2.8%
8 3
 
2.1%
9 3
 
2.1%
15 3
 
2.1%
Other values (10) 11
 
7.7%
2023-12-09T22:39:11.198145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 44
28.4%
2 35
22.6%
3 27
17.4%
4 14
 
9.0%
5 13
 
8.4%
6 8
 
5.2%
0 5
 
3.2%
8 4
 
2.6%
9 3
 
1.9%
7 2
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 155
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 44
28.4%
2 35
22.6%
3 27
17.4%
4 14
 
9.0%
5 13
 
8.4%
6 8
 
5.2%
0 5
 
3.2%
8 4
 
2.6%
9 3
 
1.9%
7 2
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Common 155
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 44
28.4%
2 35
22.6%
3 27
17.4%
4 14
 
9.0%
5 13
 
8.4%
6 8
 
5.2%
0 5
 
3.2%
8 4
 
2.6%
9 3
 
1.9%
7 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 155
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 44
28.4%
2 35
22.6%
3 27
17.4%
4 14
 
9.0%
5 13
 
8.4%
6 8
 
5.2%
0 5
 
3.2%
8 4
 
2.6%
9 3
 
1.9%
7 2
 
1.3%

swdappsperseat_prog2
Text

MISSING 

Distinct15
Distinct (%)10.5%
Missing331
Missing (%)69.8%
Memory size18.6 KiB
2023-12-09T22:39:11.337891image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.034965035
Min length1

Characters and Unicode

Total characters148
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)3.5%

Sample

1st row3
2nd row4
3rd row3
4th row1
5th row1
ValueCountFrequency (%)
1 45
31.5%
3 25
17.5%
2 23
16.1%
4 19
13.3%
5 9
 
6.3%
9 5
 
3.5%
6 4
 
2.8%
7 3
 
2.1%
8 3
 
2.1%
0 2
 
1.4%
Other values (5) 5
 
3.5%
2023-12-09T22:39:11.596714image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 49
33.1%
3 25
16.9%
2 25
16.9%
4 20
13.5%
5 9
 
6.1%
6 6
 
4.1%
9 5
 
3.4%
7 3
 
2.0%
8 3
 
2.0%
0 3
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 148
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 49
33.1%
3 25
16.9%
2 25
16.9%
4 20
13.5%
5 9
 
6.1%
6 6
 
4.1%
9 5
 
3.4%
7 3
 
2.0%
8 3
 
2.0%
0 3
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Common 148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 49
33.1%
3 25
16.9%
2 25
16.9%
4 20
13.5%
5 9
 
6.1%
6 6
 
4.1%
9 5
 
3.4%
7 3
 
2.0%
8 3
 
2.0%
0 3
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 49
33.1%
3 25
16.9%
2 25
16.9%
4 20
13.5%
5 9
 
6.1%
6 6
 
4.1%
9 5
 
3.4%
7 3
 
2.0%
8 3
 
2.0%
0 3
 
2.0%

swdseats_prog2
Text

MISSING 

Distinct51
Distinct (%)35.4%
Missing330
Missing (%)69.6%
Memory size18.7 KiB
2023-12-09T22:39:11.829946image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.75
Min length1

Characters and Unicode

Total characters252
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)18.1%

Sample

1st row13
2nd row18
3rd row7
4th row42
5th row9
ValueCountFrequency (%)
6 13
 
9.0%
11 10
 
6.9%
14 7
 
4.9%
18 6
 
4.2%
12 6
 
4.2%
19 6
 
4.2%
5 5
 
3.5%
20 5
 
3.5%
17 5
 
3.5%
16 5
 
3.5%
Other values (41) 76
52.8%
2023-12-09T22:39:12.190230image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 74
29.4%
2 34
13.5%
4 25
 
9.9%
6 24
 
9.5%
5 22
 
8.7%
0 17
 
6.7%
9 16
 
6.3%
3 16
 
6.3%
8 12
 
4.8%
7 12
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 252
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 74
29.4%
2 34
13.5%
4 25
 
9.9%
6 24
 
9.5%
5 22
 
8.7%
0 17
 
6.7%
9 16
 
6.3%
3 16
 
6.3%
8 12
 
4.8%
7 12
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Common 252
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 74
29.4%
2 34
13.5%
4 25
 
9.9%
6 24
 
9.5%
5 22
 
8.7%
0 17
 
6.7%
9 16
 
6.3%
3 16
 
6.3%
8 12
 
4.8%
7 12
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 74
29.4%
2 34
13.5%
4 25
 
9.9%
6 24
 
9.5%
5 22
 
8.7%
0 17
 
6.7%
9 16
 
6.3%
3 16
 
6.3%
8 12
 
4.8%
7 12
 
4.8%

geseats_prog2
Text

MISSING 

Distinct91
Distinct (%)63.2%
Missing330
Missing (%)69.6%
Memory size18.8 KiB
2023-12-09T22:39:12.511945image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.243055556
Min length1

Characters and Unicode

Total characters323
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)44.4%

Sample

1st row34
2nd row72
3rd row23
4th row198
5th row42
ValueCountFrequency (%)
24 10
 
6.9%
49 6
 
4.2%
46 4
 
2.8%
23 4
 
2.8%
52 4
 
2.8%
74 4
 
2.8%
20 4
 
2.8%
72 3
 
2.1%
39 3
 
2.1%
84 3
 
2.1%
Other values (81) 99
68.8%
2023-12-09T22:39:12.967312image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 56
17.3%
4 46
14.2%
1 36
11.1%
5 32
9.9%
3 30
9.3%
9 29
9.0%
6 26
8.0%
8 24
7.4%
0 23
7.1%
7 21
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 323
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 56
17.3%
4 46
14.2%
1 36
11.1%
5 32
9.9%
3 30
9.3%
9 29
9.0%
6 26
8.0%
8 24
7.4%
0 23
7.1%
7 21
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 323
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 56
17.3%
4 46
14.2%
1 36
11.1%
5 32
9.9%
3 30
9.3%
9 29
9.0%
6 26
8.0%
8 24
7.4%
0 23
7.1%
7 21
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 323
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 56
17.3%
4 46
14.2%
1 36
11.1%
5 32
9.9%
3 30
9.3%
9 29
9.0%
6 26
8.0%
8 24
7.4%
0 23
7.1%
7 21
 
6.5%

gefilled_prog2
Text

MISSING 

Distinct2
Distinct (%)1.2%
Missing311
Missing (%)65.6%
Memory size19.1 KiB
2023-12-09T22:39:13.089702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters163
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row0
ValueCountFrequency (%)
0 110
67.5%
1 53
32.5%
2023-12-09T22:39:13.306925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 110
67.5%
1 53
32.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 110
67.5%
1 53
32.5%

Most occurring scripts

ValueCountFrequency (%)
Common 163
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 110
67.5%
1 53
32.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 110
67.5%
1 53
32.5%

swdfilled_prog2
Text

MISSING 

Distinct2
Distinct (%)1.2%
Missing311
Missing (%)65.6%
Memory size19.1 KiB
2023-12-09T22:39:13.411395image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters163
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
0 98
60.1%
1 65
39.9%
2023-12-09T22:39:13.634117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 98
60.1%
1 65
39.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 163
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 98
60.1%
1 65
39.9%

Most occurring scripts

ValueCountFrequency (%)
Common 163
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 98
60.1%
1 65
39.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 98
60.1%
1 65
39.9%

eligibility_prog2
Text

MISSING 

Distinct39
Distinct (%)22.4%
Missing300
Missing (%)63.3%
Memory size31.2 KiB
2023-12-09T22:39:13.906812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length208
Median length201
Mean length70.59195402
Min length31

Characters and Unicode

Total characters12283
Distinct characters60
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)6.3%

Sample

1st rowOpen to students and residents of District 1
2nd rowOpen to students and residents of District 1
3rd rowOpen to students and residents of Manhattan
4th rowOpen to students and residents of District 2
5th rowOpen to students and residents of District 2
ValueCountFrequency (%)
students 186
 
9.2%
open 174
 
8.7%
to 174
 
8.7%
and 149
 
7.4%
residents 110
 
5.5%
of 109
 
5.4%
in 91
 
4.5%
the 86
 
4.3%
district 65
 
3.2%
currently 54
 
2.7%
Other values (76) 813
40.4%
2023-12-09T22:39:14.339221image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1836
14.9%
t 1218
9.9%
e 1170
9.5%
n 1148
 
9.3%
s 980
 
8.0%
o 713
 
5.8%
r 706
 
5.7%
d 607
 
4.9%
i 551
 
4.5%
a 444
 
3.6%
Other values (50) 2910
23.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9497
77.3%
Space Separator 1837
 
15.0%
Uppercase Letter 600
 
4.9%
Other Punctuation 152
 
1.2%
Decimal Number 148
 
1.2%
Close Punctuation 23
 
0.2%
Open Punctuation 23
 
0.2%
Control 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 1218
12.8%
e 1170
12.3%
n 1148
12.1%
s 980
10.3%
o 713
7.5%
r 706
7.4%
d 607
 
6.4%
i 551
 
5.8%
a 444
 
4.7%
u 355
 
3.7%
Other values (13) 1605
16.9%
Uppercase Letter
ValueCountFrequency (%)
O 174
29.0%
D 128
21.3%
S 78
13.0%
A 69
 
11.5%
B 38
 
6.3%
I 31
 
5.2%
N 23
 
3.8%
E 16
 
2.7%
H 16
 
2.7%
C 13
 
2.2%
Other values (6) 14
 
2.3%
Decimal Number
ValueCountFrequency (%)
2 38
25.7%
1 30
20.3%
5 24
16.2%
7 14
 
9.5%
3 14
 
9.5%
6 10
 
6.8%
0 7
 
4.7%
8 5
 
3.4%
4 3
 
2.0%
9 3
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 85
55.9%
, 38
25.0%
@ 27
 
17.8%
& 1
 
0.7%
; 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1836
99.9%
  1
 
0.1%
Control
ValueCountFrequency (%)
‚ 2
66.7%
ƒ 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10097
82.2%
Common 2186
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 1218
12.1%
e 1170
11.6%
n 1148
11.4%
s 980
9.7%
o 713
 
7.1%
r 706
 
7.0%
d 607
 
6.0%
i 551
 
5.5%
a 444
 
4.4%
u 355
 
3.5%
Other values (29) 2205
21.8%
Common
ValueCountFrequency (%)
1836
84.0%
. 85
 
3.9%
2 38
 
1.7%
, 38
 
1.7%
1 30
 
1.4%
@ 27
 
1.2%
5 24
 
1.1%
) 23
 
1.1%
( 23
 
1.1%
7 14
 
0.6%
Other values (11) 48
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12275
99.9%
None 8
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1836
15.0%
t 1218
9.9%
e 1170
9.5%
n 1148
 
9.4%
s 980
 
8.0%
o 713
 
5.8%
r 706
 
5.8%
d 607
 
4.9%
i 551
 
4.5%
a 444
 
3.6%
Other values (45) 2902
23.6%
None
ValueCountFrequency (%)
à 2
25.0%
‚ 2
25.0%
 2
25.0%
ƒ 1
12.5%
  1
12.5%

priority1_prog2
Text

MISSING 

Distinct24
Distinct (%)28.9%
Missing391
Missing (%)82.5%
Memory size20.7 KiB
2023-12-09T22:39:14.590373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length97
Median length96
Mean length45.57831325
Min length31

Characters and Unicode

Total characters3783
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)16.9%

Sample

1st rowPriority to continuing students
2nd rowPriority to continuing students
3rd rowPriority to continuing students
4th rowPriority to continuing students
5th rowPriority to continuing students
ValueCountFrequency (%)
to 87
14.1%
priority 82
13.3%
students 61
 
9.9%
residents 52
 
8.5%
and 30
 
4.9%
continuing 30
 
4.9%
of 28
 
4.6%
the 27
 
4.4%
zone 27
 
4.4%
district 26
 
4.2%
Other values (35) 165
26.8%
2023-12-09T22:39:14.978059image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
532
14.1%
t 478
12.6%
i 377
10.0%
o 315
8.3%
n 307
8.1%
s 284
7.5%
e 267
 
7.1%
r 245
 
6.5%
d 196
 
5.2%
P 94
 
2.5%
Other values (28) 688
18.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3024
79.9%
Space Separator 532
 
14.1%
Uppercase Letter 139
 
3.7%
Decimal Number 80
 
2.1%
Other Punctuation 8
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 478
15.8%
i 377
12.5%
o 315
10.4%
n 307
10.2%
s 284
9.4%
e 267
8.8%
r 245
8.1%
d 196
6.5%
u 91
 
3.0%
y 82
 
2.7%
Other values (10) 382
12.6%
Decimal Number
ValueCountFrequency (%)
1 29
36.2%
8 9
 
11.2%
0 8
 
10.0%
7 7
 
8.8%
4 7
 
8.8%
3 7
 
8.8%
5 6
 
7.5%
2 5
 
6.2%
6 1
 
1.2%
9 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
P 94
67.6%
D 26
 
18.7%
S 14
 
10.1%
R 2
 
1.4%
X 2
 
1.4%
T 1
 
0.7%
Space Separator
ValueCountFrequency (%)
532
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3163
83.6%
Common 620
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 478
15.1%
i 377
11.9%
o 315
10.0%
n 307
9.7%
s 284
9.0%
e 267
8.4%
r 245
7.7%
d 196
 
6.2%
P 94
 
3.0%
u 91
 
2.9%
Other values (16) 509
16.1%
Common
ValueCountFrequency (%)
532
85.8%
1 29
 
4.7%
8 9
 
1.5%
0 8
 
1.3%
, 8
 
1.3%
7 7
 
1.1%
4 7
 
1.1%
3 7
 
1.1%
5 6
 
1.0%
2 5
 
0.8%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3783
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
532
14.1%
t 478
12.6%
i 377
10.0%
o 315
8.3%
n 307
8.1%
s 284
7.5%
e 267
 
7.1%
r 245
 
6.5%
d 196
 
5.2%
P 94
 
2.5%
Other values (28) 688
18.2%

priority2_prog2
Text

MISSING 

Distinct26
Distinct (%)32.5%
Missing394
Missing (%)83.1%
Memory size20.3 KiB
2023-12-09T22:39:15.199487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length73
Median length71
Mean length43.025
Min length36

Characters and Unicode

Total characters3442
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)12.5%

Sample

1st rowThen to District 1 students and residents
2nd rowThen to residents of the elementary school zone who sign in at an event
3rd rowThen to residents of the elementary school zone who sign in at an event
4th rowThen to residents of the elementary school zone
5th rowThen to residents of the elementary school zone
ValueCountFrequency (%)
then 80
13.6%
to 80
13.6%
residents 80
13.6%
students 60
10.2%
and 60
10.2%
district 43
7.3%
of 21
 
3.6%
the 20
 
3.4%
school 20
 
3.4%
zone 19
 
3.2%
Other values (35) 106
18.0%
2023-12-09T22:39:15.550545image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
14.8%
t 407
11.8%
e 392
11.4%
s 347
10.1%
n 343
10.0%
d 214
 
6.2%
o 186
 
5.4%
i 179
 
5.2%
r 153
 
4.4%
h 124
 
3.6%
Other values (30) 588
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2699
78.4%
Space Separator 509
 
14.8%
Uppercase Letter 146
 
4.2%
Decimal Number 86
 
2.5%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 407
15.1%
e 392
14.5%
s 347
12.9%
n 343
12.7%
d 214
7.9%
o 186
6.9%
i 179
6.6%
r 153
 
5.7%
h 124
 
4.6%
a 82
 
3.0%
Other values (12) 272
10.1%
Decimal Number
ValueCountFrequency (%)
1 27
31.4%
2 16
18.6%
0 12
14.0%
8 9
 
10.5%
3 6
 
7.0%
7 5
 
5.8%
6 5
 
5.8%
9 3
 
3.5%
5 2
 
2.3%
4 1
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
T 80
54.8%
D 43
29.5%
B 16
 
11.0%
S 3
 
2.1%
P 3
 
2.1%
M 1
 
0.7%
Space Separator
ValueCountFrequency (%)
509
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2845
82.7%
Common 597
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 407
14.3%
e 392
13.8%
s 347
12.2%
n 343
12.1%
d 214
7.5%
o 186
6.5%
i 179
6.3%
r 153
 
5.4%
h 124
 
4.4%
a 82
 
2.9%
Other values (18) 418
14.7%
Common
ValueCountFrequency (%)
509
85.3%
1 27
 
4.5%
2 16
 
2.7%
0 12
 
2.0%
8 9
 
1.5%
3 6
 
1.0%
7 5
 
0.8%
6 5
 
0.8%
9 3
 
0.5%
5 2
 
0.3%
Other values (2) 3
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509
14.8%
t 407
11.8%
e 392
11.4%
s 347
10.1%
n 343
10.0%
d 214
 
6.2%
o 186
 
5.4%
i 179
 
5.2%
r 153
 
4.4%
h 124
 
3.6%
Other values (30) 588
17.1%

priority3_prog2
Text

MISSING 

Distinct9
Distinct (%)40.9%
Missing452
Missing (%)95.4%
Memory size16.4 KiB
2023-12-09T22:39:15.757240image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length60
Mean length41.95454545
Min length36

Characters and Unicode

Total characters923
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)18.2%

Sample

1st rowThen to residents of the elementary school zone
2nd rowThen to District 3 students and residents who sign in at an event
3rd rowThen to District 3 students and residents
4th rowThen to District 4 students and residents
5th rowThen to District 4 students and residents
ValueCountFrequency (%)
then 22
13.7%
to 22
13.7%
residents 22
13.7%
students 21
13.0%
and 21
13.0%
bronx 12
7.5%
district 9
 
5.6%
event 3
 
1.9%
an 3
 
1.9%
at 3
 
1.9%
Other values (13) 23
14.3%
2023-12-09T22:39:16.086509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
15.1%
n 112
12.1%
t 112
12.1%
s 99
10.7%
e 98
10.6%
d 64
6.9%
i 46
 
5.0%
r 44
 
4.8%
o 41
 
4.4%
a 28
 
3.0%
Other values (19) 140
15.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 729
79.0%
Space Separator 139
 
15.1%
Uppercase Letter 43
 
4.7%
Decimal Number 12
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 112
15.4%
t 112
15.4%
s 99
13.6%
e 98
13.4%
d 64
8.8%
i 46
6.3%
r 44
 
6.0%
o 41
 
5.6%
a 28
 
3.8%
h 27
 
3.7%
Other values (11) 58
8.0%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
3 3
25.0%
9 2
 
16.7%
4 2
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
T 22
51.2%
B 12
27.9%
D 9
20.9%
Space Separator
ValueCountFrequency (%)
139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 772
83.6%
Common 151
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 112
14.5%
t 112
14.5%
s 99
12.8%
e 98
12.7%
d 64
8.3%
i 46
6.0%
r 44
 
5.7%
o 41
 
5.3%
a 28
 
3.6%
h 27
 
3.5%
Other values (14) 101
13.1%
Common
ValueCountFrequency (%)
139
92.1%
1 5
 
3.3%
3 3
 
2.0%
9 2
 
1.3%
4 2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 923
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
15.1%
n 112
12.1%
t 112
12.1%
s 99
10.7%
e 98
10.6%
d 64
6.9%
i 46
 
5.0%
r 44
 
4.8%
o 41
 
4.4%
a 28
 
3.0%
Other values (19) 140
15.2%

priority4_prog2
Text

MISSING 

Distinct5
Distinct (%)45.5%
Missing463
Missing (%)97.7%
Memory size15.6 KiB
2023-12-09T22:39:16.299342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length36
Mean length41
Min length36

Characters and Unicode

Total characters451
Distinct characters27
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)27.3%

Sample

1st rowThen to District 2 students and residents who sign in at an event
2nd rowThen to residents of the elementary school zone
3rd rowThen to Manhattan students and residents
4th rowThen to Manhattan students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
then 11
14.3%
residents 11
14.3%
to 11
14.3%
students 10
13.0%
and 10
13.0%
bronx 7
9.1%
manhattan 2
 
2.6%
the 2
 
2.6%
of 2
 
2.6%
an 1
 
1.3%
Other values (10) 10
13.0%
2023-12-09T22:39:16.630266image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
14.6%
n 59
13.1%
t 53
11.8%
e 51
11.3%
s 45
10.0%
d 31
6.9%
o 24
 
5.3%
r 20
 
4.4%
a 19
 
4.2%
h 17
 
3.8%
Other values (17) 66
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 363
80.5%
Space Separator 66
 
14.6%
Uppercase Letter 21
 
4.7%
Decimal Number 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 59
16.3%
t 53
14.6%
e 51
14.0%
s 45
12.4%
d 31
8.5%
o 24
6.6%
r 20
 
5.5%
a 19
 
5.2%
h 17
 
4.7%
i 15
 
4.1%
Other values (11) 29
8.0%
Uppercase Letter
ValueCountFrequency (%)
T 11
52.4%
B 7
33.3%
M 2
 
9.5%
D 1
 
4.8%
Space Separator
ValueCountFrequency (%)
66
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 384
85.1%
Common 67
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 59
15.4%
t 53
13.8%
e 51
13.3%
s 45
11.7%
d 31
8.1%
o 24
6.2%
r 20
 
5.2%
a 19
 
4.9%
h 17
 
4.4%
i 15
 
3.9%
Other values (15) 50
13.0%
Common
ValueCountFrequency (%)
66
98.5%
2 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 451
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
14.6%
n 59
13.1%
t 53
11.8%
e 51
11.3%
s 45
10.0%
d 31
6.9%
o 24
 
5.3%
r 20
 
4.4%
a 19
 
4.2%
h 17
 
3.8%
Other values (17) 66
14.6%

priority5_prog2
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.1 KiB
2023-12-09T22:39:16.816919image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length41
Mean length41
Min length41

Characters and Unicode

Total characters82
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowThen to District 2 students and residents
2nd rowThen to District 3 students and residents
ValueCountFrequency (%)
then 2
14.3%
to 2
14.3%
district 2
14.3%
students 2
14.3%
and 2
14.3%
residents 2
14.3%
3 1
7.1%
2 1
7.1%
2023-12-09T22:39:17.109432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
14.6%
t 12
14.6%
s 10
12.2%
e 8
9.8%
n 8
9.8%
i 6
7.3%
d 6
7.3%
r 4
 
4.9%
c 2
 
2.4%
a 2
 
2.4%
Other values (7) 12
14.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64
78.0%
Space Separator 12
 
14.6%
Uppercase Letter 4
 
4.9%
Decimal Number 2
 
2.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 12
18.8%
s 10
15.6%
e 8
12.5%
n 8
12.5%
i 6
9.4%
d 6
9.4%
r 4
 
6.2%
c 2
 
3.1%
a 2
 
3.1%
u 2
 
3.1%
Other values (2) 4
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
D 2
50.0%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 68
82.9%
Common 14
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 12
17.6%
s 10
14.7%
e 8
11.8%
n 8
11.8%
i 6
8.8%
d 6
8.8%
r 4
 
5.9%
c 2
 
2.9%
a 2
 
2.9%
u 2
 
2.9%
Other values (4) 8
11.8%
Common
ValueCountFrequency (%)
12
85.7%
3 1
 
7.1%
2 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
14.6%
t 12
14.6%
s 10
12.2%
e 8
9.8%
n 8
9.8%
i 6
7.3%
d 6
7.3%
r 4
 
4.9%
c 2
 
2.4%
a 2
 
2.4%
Other values (7) 12
14.6%

priority6_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

prefnote_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog2
Text

MISSING 

Distinct8
Distinct (%)20.5%
Missing435
Missing (%)91.8%
Memory size17.7 KiB
2023-12-09T22:39:17.361952image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length43
Mean length47.74358974
Min length10

Characters and Unicode

Total characters1862
Distinct characters46
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)7.7%

Sample

1st row4th Grade New York State ELA and Math Exams
2nd rowAcademic and Personal Behavior Scores
3rd rowOn-Site Assessment
4th row4th Grade New York State ELA and Math Exams
5th row4th Grade New York State ELA and Math Exams
ValueCountFrequency (%)
and 26
 
7.4%
4th 22
 
6.3%
state 22
 
6.3%
ela 22
 
6.3%
grade 22
 
6.3%
york 22
 
6.3%
new 22
 
6.3%
math 21
 
6.0%
exams 21
 
6.0%
on 12
 
3.4%
Other values (31) 137
39.3%
2023-12-09T22:39:17.736041image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
16.6%
e 175
 
9.4%
t 163
 
8.8%
a 158
 
8.5%
s 99
 
5.3%
r 90
 
4.8%
o 74
 
4.0%
h 72
 
3.9%
d 71
 
3.8%
n 63
 
3.4%
Other values (36) 587
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1246
66.9%
Space Separator 310
 
16.6%
Uppercase Letter 262
 
14.1%
Decimal Number 37
 
2.0%
Other Punctuation 4
 
0.2%
Dash Punctuation 3
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 175
14.0%
t 163
13.1%
a 158
12.7%
s 99
7.9%
r 90
 
7.2%
o 74
 
5.9%
h 72
 
5.8%
d 71
 
5.7%
n 63
 
5.1%
i 38
 
3.0%
Other values (12) 243
19.5%
Uppercase Letter
ValueCountFrequency (%)
E 46
17.6%
S 38
14.5%
A 30
11.5%
L 27
10.3%
Y 22
8.4%
N 22
8.4%
G 22
8.4%
M 22
8.4%
T 13
 
5.0%
D 6
 
2.3%
Other values (4) 14
 
5.3%
Decimal Number
ValueCountFrequency (%)
4 22
59.5%
2 8
 
21.6%
1 6
 
16.2%
5 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
/ 1
25.0%
: 1
25.0%
. 1
25.0%
% 1
25.0%
Space Separator
ValueCountFrequency (%)
310
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1508
81.0%
Common 354
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 175
 
11.6%
t 163
 
10.8%
a 158
 
10.5%
s 99
 
6.6%
r 90
 
6.0%
o 74
 
4.9%
h 72
 
4.8%
d 71
 
4.7%
n 63
 
4.2%
E 46
 
3.1%
Other values (26) 497
33.0%
Common
ValueCountFrequency (%)
310
87.6%
4 22
 
6.2%
2 8
 
2.3%
1 6
 
1.7%
- 3
 
0.8%
/ 1
 
0.3%
: 1
 
0.3%
. 1
 
0.3%
5 1
 
0.3%
% 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1862
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
16.6%
e 175
 
9.4%
t 163
 
8.8%
a 158
 
8.5%
s 99
 
5.3%
r 90
 
4.8%
o 74
 
4.0%
h 72
 
3.9%
d 71
 
3.8%
n 63
 
3.4%
Other values (36) 587
31.5%

selectioncriteria2_prog2
Text

MISSING 

Distinct6
Distinct (%)20.7%
Missing445
Missing (%)93.9%
Memory size16.4 KiB
2023-12-09T22:39:17.969274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length67
Median length41
Mean length26.55172414
Min length10

Characters and Unicode

Total characters770
Distinct characters43
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)10.3%

Sample

1st rowAcademic and Personal Behavior Scores
2nd rowAttendance
3rd rowAcademic and Personal Behavior Scores
4th rowAcademic and Personal Behavior Scores
5th rowAcademic and Personal Behavior Scores
ValueCountFrequency (%)
academic 14
13.3%
personal 14
13.3%
behavior 14
13.3%
scores 14
13.3%
and 14
13.3%
attendance 10
9.5%
home 2
 
1.9%
language 2
 
1.9%
new 1
 
1.0%
january 1
 
1.0%
Other values (19) 19
18.1%
2023-12-09T22:39:18.351985image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 89
11.6%
a 78
 
10.1%
76
 
9.9%
n 58
 
7.5%
c 54
 
7.0%
o 50
 
6.5%
r 47
 
6.1%
d 41
 
5.3%
s 36
 
4.7%
i 33
 
4.3%
Other values (33) 208
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 603
78.3%
Uppercase Letter 82
 
10.6%
Space Separator 76
 
9.9%
Decimal Number 4
 
0.5%
Other Punctuation 4
 
0.5%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 89
14.8%
a 78
12.9%
n 58
9.6%
c 54
9.0%
o 50
8.3%
r 47
7.8%
d 41
6.8%
s 36
6.0%
i 33
 
5.5%
t 31
 
5.1%
Other values (12) 86
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 27
32.9%
S 16
19.5%
P 14
17.1%
B 14
17.1%
L 2
 
2.4%
H 2
 
2.4%
Y 1
 
1.2%
E 1
 
1.2%
M 1
 
1.2%
N 1
 
1.2%
Other values (3) 3
 
3.7%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
4 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
: 1
25.0%
% 1
25.0%
Space Separator
ValueCountFrequency (%)
76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 685
89.0%
Common 85
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 89
13.0%
a 78
11.4%
n 58
 
8.5%
c 54
 
7.9%
o 50
 
7.3%
r 47
 
6.9%
d 41
 
6.0%
s 36
 
5.3%
i 33
 
4.8%
t 31
 
4.5%
Other values (25) 168
24.5%
Common
ValueCountFrequency (%)
76
89.4%
2 2
 
2.4%
. 2
 
2.4%
5 1
 
1.2%
: 1
 
1.2%
4 1
 
1.2%
- 1
 
1.2%
% 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 770
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 89
11.6%
a 78
 
10.1%
76
 
9.9%
n 58
 
7.5%
c 54
 
7.0%
o 50
 
6.5%
r 47
 
6.1%
d 41
 
5.3%
s 36
 
4.7%
i 33
 
4.3%
Other values (33) 208
27.0%

selectioncriteria3_prog2
Text

MISSING 

Distinct9
Distinct (%)34.6%
Missing448
Missing (%)94.5%
Memory size15.9 KiB
2023-12-09T22:39:18.554371image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length10
Mean length12.30769231
Min length8

Characters and Unicode

Total characters320
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)19.2%

Sample

1st rowAttendance
2nd rowFinal 4th Grade Report Card
3rd rowAttendance
4th rowAttendance
5th rowAttendance
ValueCountFrequency (%)
attendance 15
33.3%
status 3
 
6.7%
ell 3
 
6.7%
grade 2
 
4.4%
and 2
 
4.4%
report 2
 
4.4%
card 2
 
4.4%
4th 2
 
4.4%
final 2
 
4.4%
assessment 2
 
4.4%
Other values (9) 10
22.2%
2023-12-09T22:39:18.896886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 47
14.7%
e 45
14.1%
n 41
12.8%
a 31
9.7%
d 21
 
6.6%
A 19
 
5.9%
19
 
5.9%
c 16
 
5.0%
s 13
 
4.1%
L 9
 
2.8%
Other values (24) 59
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 244
76.2%
Uppercase Letter 50
 
15.6%
Space Separator 19
 
5.9%
Decimal Number 3
 
0.9%
Dash Punctuation 2
 
0.6%
Other Punctuation 2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 47
19.3%
e 45
18.4%
n 41
16.8%
a 31
12.7%
d 21
8.6%
c 16
 
6.6%
s 13
 
5.3%
r 7
 
2.9%
i 4
 
1.6%
u 4
 
1.6%
Other values (6) 15
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
A 19
38.0%
L 9
18.0%
S 5
 
10.0%
E 4
 
8.0%
C 2
 
4.0%
R 2
 
4.0%
F 2
 
4.0%
G 2
 
4.0%
O 2
 
4.0%
H 1
 
2.0%
Other values (2) 2
 
4.0%
Decimal Number
ValueCountFrequency (%)
4 2
66.7%
5 1
33.3%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 294
91.9%
Common 26
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 47
16.0%
e 45
15.3%
n 41
13.9%
a 31
10.5%
d 21
7.1%
A 19
6.5%
c 16
 
5.4%
s 13
 
4.4%
L 9
 
3.1%
r 7
 
2.4%
Other values (18) 45
15.3%
Common
ValueCountFrequency (%)
19
73.1%
4 2
 
7.7%
- 2
 
7.7%
: 1
 
3.8%
5 1
 
3.8%
% 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 47
14.7%
e 45
14.1%
n 41
12.8%
a 31
9.7%
d 21
 
6.6%
A 19
 
5.9%
19
 
5.9%
c 16
 
5.0%
s 13
 
4.1%
L 9
 
2.8%
Other values (24) 59
18.4%

selectioncriteria4_prog2
Text

MISSING 

Distinct5
Distinct (%)25.0%
Missing454
Missing (%)95.8%
Memory size15.8 KiB
2023-12-09T22:39:19.093311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length27
Mean length21.2
Min length8

Characters and Unicode

Total characters424
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)10.0%

Sample

1st rowFinal 4th Grade Report Card
2nd rowLateness
3rd rowFinal 4th Grade Report Card
4th rowFinal 4th Grade Report Card
5th rowFinal 4th Grade Report Card
ValueCountFrequency (%)
final 13
17.1%
4th 13
17.1%
grade 13
17.1%
report 13
17.1%
card 13
17.1%
lateness 4
 
5.3%
home 2
 
2.6%
language 2
 
2.6%
ell 1
 
1.3%
status 1
 
1.3%
2023-12-09T22:39:19.410368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
13.2%
a 48
 
11.3%
r 39
 
9.2%
e 38
 
9.0%
t 32
 
7.5%
d 26
 
6.1%
n 19
 
4.5%
o 15
 
3.5%
4 14
 
3.3%
F 13
 
3.1%
Other values (18) 124
29.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 287
67.7%
Uppercase Letter 64
 
15.1%
Space Separator 56
 
13.2%
Decimal Number 15
 
3.5%
Other Punctuation 2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 48
16.7%
r 39
13.6%
e 38
13.2%
t 32
11.1%
d 26
9.1%
n 19
 
6.6%
o 15
 
5.2%
i 13
 
4.5%
p 13
 
4.5%
h 13
 
4.5%
Other values (5) 31
10.8%
Uppercase Letter
ValueCountFrequency (%)
F 13
20.3%
R 13
20.3%
C 13
20.3%
G 13
20.3%
L 8
12.5%
H 2
 
3.1%
E 1
 
1.6%
S 1
 
1.6%
Decimal Number
ValueCountFrequency (%)
4 14
93.3%
5 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 351
82.8%
Common 73
 
17.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 48
13.7%
r 39
11.1%
e 38
 
10.8%
t 32
 
9.1%
d 26
 
7.4%
n 19
 
5.4%
o 15
 
4.3%
F 13
 
3.7%
R 13
 
3.7%
C 13
 
3.7%
Other values (13) 95
27.1%
Common
ValueCountFrequency (%)
56
76.7%
4 14
 
19.2%
: 1
 
1.4%
5 1
 
1.4%
% 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
13.2%
a 48
 
11.3%
r 39
 
9.2%
e 38
 
9.0%
t 32
 
7.5%
d 26
 
6.1%
n 19
 
4.5%
o 15
 
3.5%
4 14
 
3.3%
F 13
 
3.1%
Other values (18) 124
29.2%

selectioncriteria5_prog2
Text

MISSING 

Distinct4
Distinct (%)28.6%
Missing460
Missing (%)97.0%
Memory size15.4 KiB
2023-12-09T22:39:20.037411image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length8
Mean length9.571428571
Min length8

Characters and Unicode

Total characters134
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)21.4%

Sample

1st rowLateness
2nd rowLateness
3rd rowLateness
4th rowLateness
5th rowLateness
ValueCountFrequency (%)
lateness 11
64.7%
on-site 1
 
5.9%
assessment 1
 
5.9%
punctuality 1
 
5.9%
5 1
 
5.9%
home 1
 
5.9%
language 1
 
5.9%
2023-12-09T22:39:20.322872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 27
20.1%
s 26
19.4%
t 15
11.2%
n 15
11.2%
a 14
10.4%
L 12
9.0%
u 3
 
2.2%
3
 
2.2%
i 2
 
1.5%
m 2
 
1.5%
Other values (14) 15
11.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 110
82.1%
Uppercase Letter 17
 
12.7%
Space Separator 3
 
2.2%
Other Punctuation 2
 
1.5%
Dash Punctuation 1
 
0.7%
Decimal Number 1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 27
24.5%
s 26
23.6%
t 15
13.6%
n 15
13.6%
a 14
12.7%
u 3
 
2.7%
i 2
 
1.8%
m 2
 
1.8%
g 2
 
1.8%
c 1
 
0.9%
Other values (3) 3
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
L 12
70.6%
S 1
 
5.9%
A 1
 
5.9%
P 1
 
5.9%
O 1
 
5.9%
H 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 127
94.8%
Common 7
 
5.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 27
21.3%
s 26
20.5%
t 15
11.8%
n 15
11.8%
a 14
11.0%
L 12
9.4%
u 3
 
2.4%
i 2
 
1.6%
m 2
 
1.6%
g 2
 
1.6%
Other values (9) 9
 
7.1%
Common
ValueCountFrequency (%)
3
42.9%
- 1
 
14.3%
: 1
 
14.3%
5 1
 
14.3%
% 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 27
20.1%
s 26
19.4%
t 15
11.2%
n 15
11.2%
a 14
10.4%
L 12
9.0%
u 3
 
2.2%
3
 
2.2%
i 2
 
1.5%
m 2
 
1.5%
Other values (14) 15
11.2%

selectioncriteria6_prog2
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.2 KiB
2023-12-09T22:39:20.498032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length55
Median length18
Mean length23.4
Min length8

Characters and Unicode

Total characters117
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowOn-Site Assessment
2nd rowOn-Site Assessment
3rd rowOn-Site Assessment
4th rowMath and English Assessment - Multiple choice and Essay
5th rowLateness
ValueCountFrequency (%)
assessment 4
25.0%
on-site 3
18.8%
and 2
12.5%
lateness 1
 
6.2%
math 1
 
6.2%
english 1
 
6.2%
1
 
6.2%
multiple 1
 
6.2%
choice 1
 
6.2%
essay 1
 
6.2%
2023-12-09T22:39:20.786074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 21
17.9%
e 15
12.8%
n 11
9.4%
11
9.4%
t 10
 
8.5%
i 6
 
5.1%
a 5
 
4.3%
- 4
 
3.4%
A 4
 
3.4%
m 4
 
3.4%
Other values (14) 26
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 87
74.4%
Uppercase Letter 15
 
12.8%
Space Separator 11
 
9.4%
Dash Punctuation 4
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 21
24.1%
e 15
17.2%
n 11
12.6%
t 10
11.5%
i 6
 
6.9%
a 5
 
5.7%
m 4
 
4.6%
l 3
 
3.4%
h 3
 
3.4%
d 2
 
2.3%
Other values (6) 7
 
8.0%
Uppercase Letter
ValueCountFrequency (%)
A 4
26.7%
O 3
20.0%
S 3
20.0%
M 2
13.3%
E 2
13.3%
L 1
 
6.7%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 102
87.2%
Common 15
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 21
20.6%
e 15
14.7%
n 11
10.8%
t 10
9.8%
i 6
 
5.9%
a 5
 
4.9%
A 4
 
3.9%
m 4
 
3.9%
l 3
 
2.9%
h 3
 
2.9%
Other values (12) 20
19.6%
Common
ValueCountFrequency (%)
11
73.3%
- 4
 
26.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 117
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 21
17.9%
e 15
12.8%
n 11
9.4%
11
9.4%
t 10
 
8.5%
i 6
 
5.1%
a 5
 
4.3%
- 4
 
3.4%
A 4
 
3.4%
m 4
 
3.4%
Other values (14) 26
22.2%

selectioncriteria7_prog2
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:20.961947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOn-Site Assessment
ValueCountFrequency (%)
on-site 1
50.0%
assessment 1
50.0%
2023-12-09T22:39:21.251808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
72.2%
Uppercase Letter 3
 
16.7%
Dash Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 3
23.1%
n 2
15.4%
t 2
15.4%
i 1
 
7.7%
m 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
S 1
33.3%
A 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
25.0%
e 3
18.8%
n 2
12.5%
t 2
12.5%
O 1
 
6.2%
S 1
 
6.2%
i 1
 
6.2%
A 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

selectioncriteria8_prog2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog3
Text

MISSING 

Distinct59
Distinct (%)100.0%
Missing415
Missing (%)87.6%
Memory size16.7 KiB
2023-12-09T22:39:21.555124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.101694915
Min length5

Characters and Unicode

Total characters301
Distinct characters26
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)100.0%

Sample

1st rowM332Y
2nd rowM131P
3rd rowM206Y
4th rowM372M
5th rowM319U
ValueCountFrequency (%)
m372m 1
 
1.7%
k220u 1
 
1.7%
r034z 1
 
1.7%
k071y 1
 
1.7%
k084y 1
 
1.7%
k162z 1
 
1.7%
m131p 1
 
1.7%
k285z 1
 
1.7%
x229z 1
 
1.7%
r061u 1
 
1.7%
Other values (49) 49
83.1%
2023-12-09T22:39:21.985618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 32
 
10.6%
0 29
 
9.6%
2 28
 
9.3%
K 25
 
8.3%
3 21
 
7.0%
8 17
 
5.6%
Z 16
 
5.3%
7 16
 
5.3%
X 14
 
4.7%
Y 14
 
4.7%
Other values (16) 89
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 177
58.8%
Uppercase Letter 124
41.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 25
20.2%
Z 16
12.9%
X 14
11.3%
Y 14
11.3%
M 11
8.9%
Q 11
8.9%
U 11
8.9%
R 6
 
4.8%
S 4
 
3.2%
C 3
 
2.4%
Other values (6) 9
 
7.3%
Decimal Number
ValueCountFrequency (%)
1 32
18.1%
0 29
16.4%
2 28
15.8%
3 21
11.9%
8 17
9.6%
7 16
9.0%
4 11
 
6.2%
6 11
 
6.2%
9 8
 
4.5%
5 4
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 177
58.8%
Latin 124
41.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 25
20.2%
Z 16
12.9%
X 14
11.3%
Y 14
11.3%
M 11
8.9%
Q 11
8.9%
U 11
8.9%
R 6
 
4.8%
S 4
 
3.2%
C 3
 
2.4%
Other values (6) 9
 
7.3%
Common
ValueCountFrequency (%)
1 32
18.1%
0 29
16.4%
2 28
15.8%
3 21
11.9%
8 17
9.6%
7 16
9.0%
4 11
 
6.2%
6 11
 
6.2%
9 8
 
4.5%
5 4
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 32
 
10.6%
0 29
 
9.6%
2 28
 
9.3%
K 25
 
8.3%
3 21
 
7.0%
8 17
 
5.6%
Z 16
 
5.3%
7 16
 
5.3%
X 14
 
4.7%
Y 14
 
4.7%
Other values (16) 89
29.6%

name_prog3
Text

MISSING 

Distinct55
Distinct (%)93.2%
Missing415
Missing (%)87.6%
Memory size18.4 KiB
2023-12-09T22:39:22.431680image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length68
Median length45
Mean length34.94915254
Min length7

Characters and Unicode

Total characters2062
Distinct characters66
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)91.5%

Sample

1st rowUNIVERSITY NEIGHBORHOOD MIDDLE SCHOOL ASD NEST PROGRAM
2nd rowM.S. 131 Mandarin Dual Language Program
3rd rowJOSE CELSO BARBOSA ASD NEST PROGRAM
4th rowSpanish Dual Language Program
5th rowMaria Teresa Mirabal (M.S. 319)
ValueCountFrequency (%)
program 41
 
12.7%
i.s 19
 
5.9%
zoned 11
 
3.4%
asd 9
 
2.8%
school 9
 
2.8%
12:1:1 8
 
2.5%
aces 8
 
2.5%
nest 8
 
2.5%
academy 6
 
1.9%
magnet 6
 
1.9%
Other values (156) 197
61.2%
2023-12-09T22:39:23.034745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
264
 
12.8%
r 99
 
4.8%
a 98
 
4.8%
e 95
 
4.6%
S 91
 
4.4%
o 85
 
4.1%
A 75
 
3.6%
. 70
 
3.4%
n 60
 
2.9%
P 59
 
2.9%
Other values (56) 1066
51.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 832
40.3%
Uppercase Letter 717
34.8%
Space Separator 264
 
12.8%
Decimal Number 105
 
5.1%
Other Punctuation 93
 
4.5%
Close Punctuation 25
 
1.2%
Open Punctuation 25
 
1.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 91
12.7%
A 75
10.5%
P 59
 
8.2%
R 56
 
7.8%
E 55
 
7.7%
M 49
 
6.8%
O 47
 
6.6%
I 39
 
5.4%
D 32
 
4.5%
L 31
 
4.3%
Other values (16) 183
25.5%
Lowercase Letter
ValueCountFrequency (%)
r 99
11.9%
a 98
11.8%
e 95
11.4%
o 85
10.2%
n 60
 
7.2%
d 44
 
5.3%
l 43
 
5.2%
g 42
 
5.0%
i 42
 
5.0%
m 41
 
4.9%
Other values (13) 183
22.0%
Decimal Number
ValueCountFrequency (%)
1 35
33.3%
2 20
19.0%
3 11
 
10.5%
8 9
 
8.6%
7 8
 
7.6%
9 7
 
6.7%
0 6
 
5.7%
4 4
 
3.8%
6 4
 
3.8%
5 1
 
1.0%
Other Punctuation
ValueCountFrequency (%)
. 70
75.3%
: 19
 
20.4%
/ 4
 
4.3%
Space Separator
ValueCountFrequency (%)
264
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1549
75.1%
Common 513
 
24.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 99
 
6.4%
a 98
 
6.3%
e 95
 
6.1%
S 91
 
5.9%
o 85
 
5.5%
A 75
 
4.8%
n 60
 
3.9%
P 59
 
3.8%
R 56
 
3.6%
E 55
 
3.6%
Other values (39) 776
50.1%
Common
ValueCountFrequency (%)
264
51.5%
. 70
 
13.6%
1 35
 
6.8%
) 25
 
4.9%
( 25
 
4.9%
2 20
 
3.9%
: 19
 
3.7%
3 11
 
2.1%
8 9
 
1.8%
7 8
 
1.6%
Other values (7) 27
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2062
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
264
 
12.8%
r 99
 
4.8%
a 98
 
4.8%
e 95
 
4.6%
S 91
 
4.4%
o 85
 
4.1%
A 75
 
3.6%
. 70
 
3.4%
n 60
 
2.9%
P 59
 
2.9%
Other values (56) 1066
51.7%

admissionsmethod_prog3
Text

MISSING 

Distinct7
Distinct (%)11.9%
Missing415
Missing (%)87.6%
Memory size16.9 KiB
2023-12-09T22:39:23.228310image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length16
Mean length9.305084746
Min length4

Characters and Unicode

Total characters549
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)1.7%

Sample

1st rowASD/ACES Program
2nd rowScreened: Language
3rd rowASD/ACES Program
4th rowScreened: Language
5th rowOpen
ValueCountFrequency (%)
asd/aces 17
20.0%
program 17
20.0%
zoned 16
18.8%
open 14
16.5%
talent 6
 
7.1%
test 6
 
7.1%
screened 5
 
5.9%
language 2
 
2.4%
composite 1
 
1.2%
score 1
 
1.2%
2023-12-09T22:39:23.546763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 61
 
11.1%
n 43
 
7.8%
r 40
 
7.3%
S 40
 
7.3%
o 36
 
6.6%
A 34
 
6.2%
a 27
 
4.9%
26
 
4.7%
g 21
 
3.8%
d 21
 
3.8%
Other values (18) 200
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 317
57.7%
Uppercase Letter 187
34.1%
Space Separator 26
 
4.7%
Other Punctuation 19
 
3.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 61
19.2%
n 43
13.6%
r 40
12.6%
o 36
11.4%
a 27
8.5%
g 21
 
6.6%
d 21
 
6.6%
m 18
 
5.7%
p 15
 
4.7%
t 13
 
4.1%
Other values (5) 22
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
S 40
21.4%
A 34
18.2%
C 18
9.6%
E 17
9.1%
D 17
9.1%
P 17
9.1%
Z 16
 
8.6%
O 14
 
7.5%
T 12
 
6.4%
L 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 17
89.5%
: 2
 
10.5%
Space Separator
ValueCountFrequency (%)
26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 504
91.8%
Common 45
 
8.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 61
 
12.1%
n 43
 
8.5%
r 40
 
7.9%
S 40
 
7.9%
o 36
 
7.1%
A 34
 
6.7%
a 27
 
5.4%
g 21
 
4.2%
d 21
 
4.2%
C 18
 
3.6%
Other values (15) 163
32.3%
Common
ValueCountFrequency (%)
26
57.8%
/ 17
37.8%
: 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 549
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 61
 
11.1%
n 43
 
7.8%
r 40
 
7.3%
S 40
 
7.3%
o 36
 
6.6%
A 34
 
6.2%
a 27
 
4.9%
26
 
4.7%
g 21
 
3.8%
d 21
 
3.8%
Other values (18) 200
36.4%

geapps_prog3
Text

MISSING 

Distinct41
Distinct (%)97.6%
Missing432
Missing (%)91.1%
Memory size16.1 KiB
2023-12-09T22:39:23.785746image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.738095238
Min length2

Characters and Unicode

Total characters115
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)95.2%

Sample

1st row94
2nd row22
3rd row280
4th row459
5th row11
ValueCountFrequency (%)
59 2
 
4.8%
202 1
 
2.4%
94 1
 
2.4%
346 1
 
2.4%
519 1
 
2.4%
1432 1
 
2.4%
481 1
 
2.4%
98 1
 
2.4%
377 1
 
2.4%
723 1
 
2.4%
Other values (31) 31
73.8%
2023-12-09T22:39:24.166984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
19.1%
5 15
13.0%
2 13
11.3%
3 13
11.3%
8 11
9.6%
4 11
9.6%
9 10
8.7%
7 10
8.7%
0 7
 
6.1%
6 3
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 115
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
19.1%
5 15
13.0%
2 13
11.3%
3 13
11.3%
8 11
9.6%
4 11
9.6%
9 10
8.7%
7 10
8.7%
0 7
 
6.1%
6 3
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Common 115
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
19.1%
5 15
13.0%
2 13
11.3%
3 13
11.3%
8 11
9.6%
4 11
9.6%
9 10
8.7%
7 10
8.7%
0 7
 
6.1%
6 3
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
19.1%
5 15
13.0%
2 13
11.3%
3 13
11.3%
8 11
9.6%
4 11
9.6%
9 10
8.7%
7 10
8.7%
0 7
 
6.1%
6 3
 
2.6%

swdapps_prog3
Text

MISSING 

Distinct34
Distinct (%)81.0%
Missing432
Missing (%)91.1%
Memory size16.0 KiB
2023-12-09T22:39:24.397540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.952380952
Min length1

Characters and Unicode

Total characters82
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)64.3%

Sample

1st row26
2nd row5
3rd row78
4th row93
5th row11
ValueCountFrequency (%)
26 3
 
7.1%
73 2
 
4.8%
16 2
 
4.8%
65 2
 
4.8%
5 2
 
4.8%
6 2
 
4.8%
59 2
 
4.8%
14 1
 
2.4%
72 1
 
2.4%
57 1
 
2.4%
Other values (24) 24
57.1%
2023-12-09T22:39:24.763068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.1%
2 12
14.6%
6 10
12.2%
5 9
11.0%
7 8
9.8%
3 8
9.8%
4 7
8.5%
9 5
 
6.1%
8 5
 
6.1%
0 4
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
17.1%
2 12
14.6%
6 10
12.2%
5 9
11.0%
7 8
9.8%
3 8
9.8%
4 7
8.5%
9 5
 
6.1%
8 5
 
6.1%
0 4
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
Common 82
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.1%
2 12
14.6%
6 10
12.2%
5 9
11.0%
7 8
9.8%
3 8
9.8%
4 7
8.5%
9 5
 
6.1%
8 5
 
6.1%
0 4
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.1%
2 12
14.6%
6 10
12.2%
5 9
11.0%
7 8
9.8%
3 8
9.8%
4 7
8.5%
9 5
 
6.1%
8 5
 
6.1%
0 4
 
4.9%

geappsperseat_prog3
Text

MISSING 

Distinct11
Distinct (%)26.2%
Missing432
Missing (%)91.1%
Memory size16.0 KiB
2023-12-09T22:39:24.910432image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.095238095
Min length1

Characters and Unicode

Total characters46
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.8%

Sample

1st row2
2nd row1
3rd row3
4th row7
5th row0
ValueCountFrequency (%)
2 11
26.2%
1 9
21.4%
3 6
14.3%
7 3
 
7.1%
4 3
 
7.1%
5 2
 
4.8%
14 2
 
4.8%
6 2
 
4.8%
24 2
 
4.8%
0 1
 
2.4%
2023-12-09T22:39:25.169971image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
28.3%
1 11
23.9%
4 7
15.2%
3 6
13.0%
7 3
 
6.5%
5 2
 
4.3%
6 2
 
4.3%
0 1
 
2.2%
8 1
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
28.3%
1 11
23.9%
4 7
15.2%
3 6
13.0%
7 3
 
6.5%
5 2
 
4.3%
6 2
 
4.3%
0 1
 
2.2%
8 1
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common 46
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
28.3%
1 11
23.9%
4 7
15.2%
3 6
13.0%
7 3
 
6.5%
5 2
 
4.3%
6 2
 
4.3%
0 1
 
2.2%
8 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
28.3%
1 11
23.9%
4 7
15.2%
3 6
13.0%
7 3
 
6.5%
5 2
 
4.3%
6 2
 
4.3%
0 1
 
2.2%
8 1
 
2.2%

swdappsperseat_prog3
Text

MISSING 

Distinct6
Distinct (%)14.3%
Missing432
Missing (%)91.1%
Memory size16.0 KiB
2023-12-09T22:39:25.285005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.023809524
Min length1

Characters and Unicode

Total characters43
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row2
2nd row1
3rd row4
4th row4
5th row2
ValueCountFrequency (%)
1 15
35.7%
4 8
19.0%
2 8
19.0%
3 6
 
14.3%
5 4
 
9.5%
13 1
 
2.4%
2023-12-09T22:39:25.507703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
37.2%
4 8
18.6%
2 8
18.6%
3 7
16.3%
5 4
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
37.2%
4 8
18.6%
2 8
18.6%
3 7
16.3%
5 4
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
Common 43
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
37.2%
4 8
18.6%
2 8
18.6%
3 7
16.3%
5 4
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
37.2%
4 8
18.6%
2 8
18.6%
3 7
16.3%
5 4
 
9.3%

swdseats_prog3
Text

MISSING 

Distinct25
Distinct (%)59.5%
Missing432
Missing (%)91.1%
Memory size16.0 KiB
2023-12-09T22:39:25.688114image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.761904762
Min length1

Characters and Unicode

Total characters74
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)35.7%

Sample

1st row13
2nd row6
3rd row21
4th row21
5th row6
ValueCountFrequency (%)
6 6
 
14.3%
21 4
 
9.5%
10 3
 
7.1%
14 2
 
4.8%
28 2
 
4.8%
23 2
 
4.8%
18 2
 
4.8%
8 2
 
4.8%
13 2
 
4.8%
5 2
 
4.8%
Other values (15) 15
35.7%
2023-12-09T22:39:26.003872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
27.0%
2 12
16.2%
8 10
13.5%
6 8
 
10.8%
3 7
 
9.5%
4 7
 
9.5%
0 5
 
6.8%
5 3
 
4.1%
9 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
27.0%
2 12
16.2%
8 10
13.5%
6 8
 
10.8%
3 7
 
9.5%
4 7
 
9.5%
0 5
 
6.8%
5 3
 
4.1%
9 2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 74
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
27.0%
2 12
16.2%
8 10
13.5%
6 8
 
10.8%
3 7
 
9.5%
4 7
 
9.5%
0 5
 
6.8%
5 3
 
4.1%
9 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
27.0%
2 12
16.2%
8 10
13.5%
6 8
 
10.8%
3 7
 
9.5%
4 7
 
9.5%
0 5
 
6.8%
5 3
 
4.1%
9 2
 
2.7%

geseats_prog3
Text

MISSING 

Distinct37
Distinct (%)88.1%
Missing432
Missing (%)91.1%
Memory size16.1 KiB
2023-12-09T22:39:26.228124image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.285714286
Min length2

Characters and Unicode

Total characters96
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)81.0%

Sample

1st row47
2nd row17
3rd row95
4th row69
5th row25
ValueCountFrequency (%)
22 4
 
9.5%
69 2
 
4.8%
39 2
 
4.8%
56 1
 
2.4%
72 1
 
2.4%
59 1
 
2.4%
149 1
 
2.4%
32 1
 
2.4%
31 1
 
2.4%
84 1
 
2.4%
Other values (27) 27
64.3%
2023-12-09T22:39:26.575601image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 21
21.9%
1 14
14.6%
9 9
9.4%
3 8
 
8.3%
6 8
 
8.3%
5 8
 
8.3%
7 8
 
8.3%
0 7
 
7.3%
4 7
 
7.3%
8 6
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 96
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 21
21.9%
1 14
14.6%
9 9
9.4%
3 8
 
8.3%
6 8
 
8.3%
5 8
 
8.3%
7 8
 
8.3%
0 7
 
7.3%
4 7
 
7.3%
8 6
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 96
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 21
21.9%
1 14
14.6%
9 9
9.4%
3 8
 
8.3%
6 8
 
8.3%
5 8
 
8.3%
7 8
 
8.3%
0 7
 
7.3%
4 7
 
7.3%
8 6
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 21
21.9%
1 14
14.6%
9 9
9.4%
3 8
 
8.3%
6 8
 
8.3%
5 8
 
8.3%
7 8
 
8.3%
0 7
 
7.3%
4 7
 
7.3%
8 6
 
6.2%

gefilled_prog3
Text

MISSING 

Distinct2
Distinct (%)3.4%
Missing416
Missing (%)87.8%
Memory size16.4 KiB
2023-12-09T22:39:26.691752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters58
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%
2023-12-09T22:39:26.922479image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

swdfilled_prog3
Text

MISSING 

Distinct2
Distinct (%)3.4%
Missing416
Missing (%)87.8%
Memory size16.4 KiB
2023-12-09T22:39:27.032921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters58
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row1
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%
2023-12-09T22:39:27.256367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring scripts

ValueCountFrequency (%)
Common 58
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 44
75.9%
1 14
 
24.1%

eligibility_prog3
Text

MISSING 

Distinct20
Distinct (%)33.9%
Missing415
Missing (%)87.6%
Memory size21.6 KiB
2023-12-09T22:39:27.505328image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length208
Median length200
Mean length91.03389831
Min length31

Characters and Unicode

Total characters5371
Distinct characters52
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)20.3%

Sample

1st rowOpen to students currently in an ASD (Autism Spectrum Disorder) Nest program. If you are not currently an ASD Nest student and are interested in the program, please contact asdprograms@schools.nyc.gov
2nd rowOpen to students and residents of Manhattan
3rd rowOpen to students currently in an ASD (Autism Spectrum Disorder) Nest program. If you are not currently an ASD Nest student and are interested in the program, please contact asdprograms@schools.nyc.gov
4th rowOpen to students and residents of District 4
5th rowOpen to students and residents of District 6
ValueCountFrequency (%)
to 61
 
7.1%
students 60
 
6.9%
open 59
 
6.8%
and 59
 
6.8%
in 44
 
5.1%
the 36
 
4.2%
an 34
 
3.9%
are 34
 
3.9%
program 34
 
3.9%
currently 34
 
3.9%
Other values (55) 409
47.3%
2023-12-09T22:39:27.890784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
805
15.0%
t 487
 
9.1%
e 484
 
9.0%
n 448
 
8.3%
s 395
 
7.4%
r 339
 
6.3%
o 280
 
5.2%
a 260
 
4.8%
d 223
 
4.2%
i 194
 
3.6%
Other values (42) 1456
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4016
74.8%
Space Separator 805
 
15.0%
Uppercase Letter 323
 
6.0%
Other Punctuation 127
 
2.4%
Decimal Number 66
 
1.2%
Close Punctuation 17
 
0.3%
Open Punctuation 17
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 487
12.1%
e 484
12.1%
n 448
11.2%
s 395
9.8%
r 339
8.4%
o 280
 
7.0%
a 260
 
6.5%
d 223
 
5.6%
i 194
 
4.8%
c 154
 
3.8%
Other values (13) 752
18.7%
Uppercase Letter
ValueCountFrequency (%)
S 61
18.9%
O 59
18.3%
A 51
15.8%
D 46
14.2%
C 25
7.7%
E 24
 
7.4%
I 21
 
6.5%
N 17
 
5.3%
B 9
 
2.8%
P 6
 
1.9%
Other values (3) 4
 
1.2%
Decimal Number
ValueCountFrequency (%)
1 26
39.4%
2 13
19.7%
3 6
 
9.1%
6 5
 
7.6%
0 4
 
6.1%
5 4
 
6.1%
4 4
 
6.1%
9 2
 
3.0%
8 1
 
1.5%
7 1
 
1.5%
Other Punctuation
ValueCountFrequency (%)
. 71
55.9%
, 39
30.7%
@ 17
 
13.4%
Space Separator
ValueCountFrequency (%)
805
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4339
80.8%
Common 1032
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 487
11.2%
e 484
11.2%
n 448
10.3%
s 395
 
9.1%
r 339
 
7.8%
o 280
 
6.5%
a 260
 
6.0%
d 223
 
5.1%
i 194
 
4.5%
c 154
 
3.5%
Other values (26) 1075
24.8%
Common
ValueCountFrequency (%)
805
78.0%
. 71
 
6.9%
, 39
 
3.8%
1 26
 
2.5%
@ 17
 
1.6%
) 17
 
1.6%
( 17
 
1.6%
2 13
 
1.3%
3 6
 
0.6%
6 5
 
0.5%
Other values (6) 16
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5371
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
805
15.0%
t 487
 
9.1%
e 484
 
9.0%
n 448
 
8.3%
s 395
 
7.4%
r 339
 
6.3%
o 280
 
5.2%
a 260
 
4.8%
d 223
 
4.2%
i 194
 
3.6%
Other values (42) 1456
27.1%

priority1_prog3
Text

MISSING 

Distinct5
Distinct (%)38.5%
Missing461
Missing (%)97.3%
Memory size15.9 KiB
2023-12-09T22:39:28.110611image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length97
Median length47
Mean length52.61538462
Min length45

Characters and Unicode

Total characters684
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)30.8%

Sample

1st rowPriority to students attending PS 8, PS 153, or PS 173 and to residents of the middle school zone
2nd rowPriority to students attending or zoned to PS 14, PS 71, PS 72, or PS 304
3rd rowPriority to District 9 students and residents
4th rowPriority to residents of the middle school zone
5th rowPriority to residents of the middle school zone
ValueCountFrequency (%)
to 15
12.4%
priority 13
10.7%
residents 12
9.9%
of 10
8.3%
the 10
8.3%
middle 10
8.3%
school 10
8.3%
zone 10
8.3%
ps 7
 
5.8%
students 4
 
3.3%
Other values (14) 20
16.5%
2023-12-09T22:39:28.451578image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
15.8%
o 72
10.5%
t 66
9.6%
e 61
8.9%
i 54
 
7.9%
s 44
 
6.4%
r 43
 
6.3%
d 42
 
6.1%
n 34
 
5.0%
P 20
 
2.9%
Other values (22) 140
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 523
76.5%
Space Separator 108
 
15.8%
Uppercase Letter 29
 
4.2%
Decimal Number 19
 
2.8%
Other Punctuation 5
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 72
13.8%
t 66
12.6%
e 61
11.7%
i 54
10.3%
s 44
8.4%
r 43
8.2%
d 42
8.0%
n 34
6.5%
l 20
 
3.8%
h 20
 
3.8%
Other values (8) 67
12.8%
Decimal Number
ValueCountFrequency (%)
1 6
31.6%
3 3
15.8%
7 3
15.8%
4 2
 
10.5%
8 1
 
5.3%
5 1
 
5.3%
9 1
 
5.3%
2 1
 
5.3%
0 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
P 20
69.0%
S 7
 
24.1%
D 2
 
6.9%
Space Separator
ValueCountFrequency (%)
108
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 552
80.7%
Common 132
 
19.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 72
13.0%
t 66
12.0%
e 61
11.1%
i 54
9.8%
s 44
8.0%
r 43
7.8%
d 42
7.6%
n 34
 
6.2%
P 20
 
3.6%
l 20
 
3.6%
Other values (11) 96
17.4%
Common
ValueCountFrequency (%)
108
81.8%
1 6
 
4.5%
, 5
 
3.8%
3 3
 
2.3%
7 3
 
2.3%
4 2
 
1.5%
8 1
 
0.8%
5 1
 
0.8%
9 1
 
0.8%
2 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
15.8%
o 72
10.5%
t 66
9.6%
e 61
8.9%
i 54
 
7.9%
s 44
 
6.4%
r 43
 
6.3%
d 42
 
6.1%
n 34
 
5.0%
P 20
 
2.9%
Other values (22) 140
20.5%

priority2_prog3
Text

MISSING 

Distinct8
Distinct (%)61.5%
Missing461
Missing (%)97.3%
Memory size15.8 KiB
2023-12-09T22:39:28.653976image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length40.92307692
Min length36

Characters and Unicode

Total characters532
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)38.5%

Sample

1st rowThen to District 6 students and residents
2nd rowThen to District 8 students and residents
3rd rowThen to Bronx students and residents
4th rowThen to District 10 students and residents
5th rowThen to District 10 students and residents
ValueCountFrequency (%)
then 13
14.6%
to 13
14.6%
students 13
14.6%
and 13
14.6%
residents 13
14.6%
district 11
12.4%
10 4
 
4.5%
bronx 2
 
2.2%
11 2
 
2.2%
17 1
 
1.1%
Other values (4) 4
 
4.5%
2023-12-09T22:39:28.985930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
14.3%
t 74
13.9%
s 63
11.8%
n 54
10.2%
e 52
9.8%
d 39
7.3%
i 35
6.6%
r 26
 
4.9%
o 15
 
2.8%
T 13
 
2.4%
Other values (13) 85
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 410
77.1%
Space Separator 76
 
14.3%
Uppercase Letter 26
 
4.9%
Decimal Number 20
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 74
18.0%
s 63
15.4%
n 54
13.2%
e 52
12.7%
d 39
9.5%
i 35
8.5%
r 26
 
6.3%
o 15
 
3.7%
u 13
 
3.2%
a 13
 
3.2%
Other values (3) 26
 
6.3%
Decimal Number
ValueCountFrequency (%)
1 10
50.0%
0 4
 
20.0%
8 2
 
10.0%
2 2
 
10.0%
7 1
 
5.0%
6 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
T 13
50.0%
D 11
42.3%
B 2
 
7.7%
Space Separator
ValueCountFrequency (%)
76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 436
82.0%
Common 96
 
18.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 74
17.0%
s 63
14.4%
n 54
12.4%
e 52
11.9%
d 39
8.9%
i 35
8.0%
r 26
 
6.0%
o 15
 
3.4%
T 13
 
3.0%
u 13
 
3.0%
Other values (6) 52
11.9%
Common
ValueCountFrequency (%)
76
79.2%
1 10
 
10.4%
0 4
 
4.2%
8 2
 
2.1%
2 2
 
2.1%
7 1
 
1.0%
6 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
14.3%
t 74
13.9%
s 63
11.8%
n 54
10.2%
e 52
9.8%
d 39
7.3%
i 35
6.6%
r 26
 
4.9%
o 15
 
2.8%
T 13
 
2.4%
Other values (13) 85
16.0%

priority3_prog3
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)14.3%
Missing467
Missing (%)98.5%
Memory size15.4 KiB
2023-12-09T22:39:29.172853image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters252
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThen to Bronx students and residents
2nd rowThen to Bronx students and residents
3rd rowThen to Bronx students and residents
4th rowThen to Bronx students and residents
5th rowThen to Bronx students and residents
ValueCountFrequency (%)
then 7
16.7%
to 7
16.7%
bronx 7
16.7%
students 7
16.7%
and 7
16.7%
residents 7
16.7%
2023-12-09T22:39:29.471869image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 35
13.9%
35
13.9%
e 28
11.1%
t 28
11.1%
s 28
11.1%
d 21
8.3%
o 14
 
5.6%
r 14
 
5.6%
T 7
 
2.8%
h 7
 
2.8%
Other values (5) 35
13.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 203
80.6%
Space Separator 35
 
13.9%
Uppercase Letter 14
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 35
17.2%
e 28
13.8%
t 28
13.8%
s 28
13.8%
d 21
10.3%
o 14
 
6.9%
r 14
 
6.9%
h 7
 
3.4%
x 7
 
3.4%
u 7
 
3.4%
Other values (2) 14
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
T 7
50.0%
B 7
50.0%
Space Separator
ValueCountFrequency (%)
35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 217
86.1%
Common 35
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 35
16.1%
e 28
12.9%
t 28
12.9%
s 28
12.9%
d 21
9.7%
o 14
 
6.5%
r 14
 
6.5%
T 7
 
3.2%
h 7
 
3.2%
B 7
 
3.2%
Other values (4) 28
12.9%
Common
ValueCountFrequency (%)
35
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 252
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 35
13.9%
35
13.9%
e 28
11.1%
t 28
11.1%
s 28
11.1%
d 21
8.3%
o 14
 
5.6%
r 14
 
5.6%
T 7
 
2.8%
h 7
 
2.8%
Other values (5) 35
13.9%

priority4_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

prefnote_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog3
Text

MISSING 

Distinct4
Distinct (%)33.3%
Missing462
Missing (%)97.5%
Memory size16.1 KiB
2023-12-09T22:39:29.698762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length106
Mean length75.16666667
Min length40

Characters and Unicode

Total characters902
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row4th Grade New York State ELA and Math Exams
2nd row4th Grade New York State ELA and Math Exams
3rd row4th Grade New York State ELA and Math Exams
4th row4th Grade New York State ELA and Math Exams
5th row4th Grade New York State ELA and Math Exams
ValueCountFrequency (%)
on 12
 
7.1%
students 6
 
3.6%
the 6
 
3.6%
ela 6
 
3.6%
state 6
 
3.6%
york 6
 
3.6%
new 6
 
3.6%
grade 6
 
3.6%
4th 6
 
3.6%
tests 6
 
3.6%
Other values (21) 102
60.7%
2023-12-09T22:39:30.060223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
156
17.3%
e 96
 
10.6%
t 89
 
9.9%
s 59
 
6.5%
a 54
 
6.0%
r 43
 
4.8%
o 42
 
4.7%
h 35
 
3.9%
l 30
 
3.3%
n 30
 
3.3%
Other values (30) 268
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 642
71.2%
Space Separator 156
 
17.3%
Uppercase Letter 79
 
8.8%
Decimal Number 21
 
2.3%
Other Punctuation 4
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 96
15.0%
t 89
13.9%
s 59
9.2%
a 54
 
8.4%
r 43
 
6.7%
o 42
 
6.5%
h 35
 
5.5%
l 30
 
4.7%
n 30
 
4.7%
d 29
 
4.5%
Other values (11) 135
21.0%
Uppercase Letter
ValueCountFrequency (%)
T 13
16.5%
E 12
15.2%
S 12
15.2%
D 6
7.6%
M 6
7.6%
A 6
7.6%
L 6
7.6%
Y 6
7.6%
N 6
7.6%
G 6
7.6%
Decimal Number
ValueCountFrequency (%)
2 8
38.1%
1 6
28.6%
4 6
28.6%
5 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
/ 1
25.0%
: 1
25.0%
. 1
25.0%
% 1
25.0%
Space Separator
ValueCountFrequency (%)
156
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 721
79.9%
Common 181
 
20.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 96
13.3%
t 89
12.3%
s 59
 
8.2%
a 54
 
7.5%
r 43
 
6.0%
o 42
 
5.8%
h 35
 
4.9%
l 30
 
4.2%
n 30
 
4.2%
d 29
 
4.0%
Other values (21) 214
29.7%
Common
ValueCountFrequency (%)
156
86.2%
2 8
 
4.4%
1 6
 
3.3%
4 6
 
3.3%
/ 1
 
0.6%
: 1
 
0.6%
. 1
 
0.6%
5 1
 
0.6%
% 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 902
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
156
17.3%
e 96
 
10.6%
t 89
 
9.9%
s 59
 
6.5%
a 54
 
6.0%
r 43
 
4.8%
o 42
 
4.7%
h 35
 
3.9%
l 30
 
3.3%
n 30
 
3.3%
Other values (30) 268
29.7%

selectioncriteria2_prog3
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:39:30.265471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length41
Median length39
Mean length28.66666667
Min length10

Characters and Unicode

Total characters172
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowAcademic and Personal Behavior Scores
2nd rowAttendance
3rd rowAcademic and Personal Behavior Scores
4th rowAcademic and Personal Behavior Scores
5th rowAttendance
ValueCountFrequency (%)
academic 3
12.0%
and 3
12.0%
personal 3
12.0%
behavior 3
12.0%
scores 3
12.0%
attendance 2
8.0%
4th 1
 
4.0%
grade 1
 
4.0%
new 1
 
4.0%
york 1
 
4.0%
Other values (4) 4
16.0%
2023-12-09T22:39:30.635889image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 19
 
11.0%
19
 
11.0%
a 18
 
10.5%
r 11
 
6.4%
c 11
 
6.4%
n 10
 
5.8%
o 10
 
5.8%
d 9
 
5.2%
t 8
 
4.7%
i 6
 
3.5%
Other values (23) 51
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 126
73.3%
Uppercase Letter 20
 
11.6%
Space Separator 19
 
11.0%
Decimal Number 4
 
2.3%
Other Punctuation 3
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 19
15.1%
a 18
14.3%
r 11
8.7%
c 11
8.7%
n 10
7.9%
o 10
7.9%
d 9
7.1%
t 8
6.3%
i 6
 
4.8%
s 6
 
4.8%
Other values (7) 18
14.3%
Uppercase Letter
ValueCountFrequency (%)
A 5
25.0%
S 4
20.0%
B 3
15.0%
P 3
15.0%
E 1
 
5.0%
M 1
 
5.0%
Y 1
 
5.0%
N 1
 
5.0%
G 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
4 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
: 1
33.3%
% 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 146
84.9%
Common 26
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 19
13.0%
a 18
12.3%
r 11
 
7.5%
c 11
 
7.5%
n 10
 
6.8%
o 10
 
6.8%
d 9
 
6.2%
t 8
 
5.5%
i 6
 
4.1%
s 6
 
4.1%
Other values (16) 38
26.0%
Common
ValueCountFrequency (%)
19
73.1%
2 2
 
7.7%
5 1
 
3.8%
. 1
 
3.8%
: 1
 
3.8%
4 1
 
3.8%
% 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 19
 
11.0%
19
 
11.0%
a 18
 
10.5%
r 11
 
6.4%
c 11
 
6.4%
n 10
 
5.8%
o 10
 
5.8%
d 9
 
5.2%
t 8
 
4.7%
i 6
 
3.5%
Other values (23) 51
29.7%

selectioncriteria3_prog3
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:39:30.811186image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length10
Mean length13.5
Min length10

Characters and Unicode

Total characters81
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)50.0%

Sample

1st rowAttendance
2nd rowELL Status
3rd rowAttendance
4th rowAttendance
5th rowFinal 4th Grade Report Card
ValueCountFrequency (%)
attendance 4
33.3%
ell 1
 
8.3%
status 1
 
8.3%
final 1
 
8.3%
4th 1
 
8.3%
grade 1
 
8.3%
report 1
 
8.3%
card 1
 
8.3%
5 1
 
8.3%
2023-12-09T22:39:31.112952image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 12
14.8%
e 10
12.3%
n 9
11.1%
a 8
9.9%
6
 
7.4%
d 6
 
7.4%
A 4
 
4.9%
c 4
 
4.9%
r 3
 
3.7%
L 2
 
2.5%
Other values (17) 17
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 59
72.8%
Uppercase Letter 12
 
14.8%
Space Separator 6
 
7.4%
Other Punctuation 2
 
2.5%
Decimal Number 2
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 12
20.3%
e 10
16.9%
n 9
15.3%
a 8
13.6%
d 6
10.2%
c 4
 
6.8%
r 3
 
5.1%
o 1
 
1.7%
p 1
 
1.7%
h 1
 
1.7%
Other values (4) 4
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
A 4
33.3%
L 2
16.7%
G 1
 
8.3%
C 1
 
8.3%
R 1
 
8.3%
F 1
 
8.3%
S 1
 
8.3%
E 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 71
87.7%
Common 10
 
12.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 12
16.9%
e 10
14.1%
n 9
12.7%
a 8
11.3%
d 6
8.5%
A 4
 
5.6%
c 4
 
5.6%
r 3
 
4.2%
L 2
 
2.8%
G 1
 
1.4%
Other values (12) 12
16.9%
Common
ValueCountFrequency (%)
6
60.0%
: 1
 
10.0%
5 1
 
10.0%
4 1
 
10.0%
% 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 12
14.8%
e 10
12.3%
n 9
11.1%
a 8
9.9%
6
 
7.4%
d 6
 
7.4%
A 4
 
4.9%
c 4
 
4.9%
r 3
 
3.7%
L 2
 
2.5%
Other values (17) 17
21.0%

selectioncriteria4_prog3
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:39:31.292976image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length32
Median length27
Mean length24.66666667
Min length8

Characters and Unicode

Total characters148
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowFinal 4th Grade Report Card
2nd rowFinal 4th Grade Report Card
3rd rowFinal 4th Grade Report Card
4th rowFinal 4th Grade Report Card
5th rowLateness
ValueCountFrequency (%)
final 5
18.5%
4th 5
18.5%
grade 5
18.5%
report 5
18.5%
card 5
18.5%
lateness 1
 
3.7%
45 1
 
3.7%
2023-12-09T22:39:31.589293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21
14.2%
a 16
 
10.8%
r 15
 
10.1%
e 12
 
8.1%
t 11
 
7.4%
d 10
 
6.8%
n 6
 
4.1%
4 6
 
4.1%
C 5
 
3.4%
o 5
 
3.4%
Other values (12) 41
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 97
65.5%
Space Separator 21
 
14.2%
Uppercase Letter 21
 
14.2%
Decimal Number 7
 
4.7%
Other Punctuation 2
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 16
16.5%
r 15
15.5%
e 12
12.4%
t 11
11.3%
d 10
10.3%
n 6
 
6.2%
o 5
 
5.2%
p 5
 
5.2%
i 5
 
5.2%
h 5
 
5.2%
Other values (2) 7
7.2%
Uppercase Letter
ValueCountFrequency (%)
C 5
23.8%
R 5
23.8%
F 5
23.8%
G 5
23.8%
L 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
4 6
85.7%
5 1
 
14.3%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 118
79.7%
Common 30
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 16
13.6%
r 15
12.7%
e 12
10.2%
t 11
 
9.3%
d 10
 
8.5%
n 6
 
5.1%
C 5
 
4.2%
o 5
 
4.2%
p 5
 
4.2%
R 5
 
4.2%
Other values (7) 28
23.7%
Common
ValueCountFrequency (%)
21
70.0%
4 6
 
20.0%
: 1
 
3.3%
5 1
 
3.3%
% 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21
14.2%
a 16
 
10.8%
r 15
 
10.1%
e 12
 
8.1%
t 11
 
7.4%
d 10
 
6.8%
n 6
 
4.1%
4 6
 
4.1%
C 5
 
3.4%
o 5
 
3.4%
Other values (12) 41
27.7%

selectioncriteria5_prog3
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:39:31.763353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length16.5
Mean length11.66666667
Min length8

Characters and Unicode

Total characters70
Distinct characters24
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)50.0%

Sample

1st rowLateness
2nd rowHome Language
3rd rowLateness
4th rowLateness
5th rowOn-Site Assessment
ValueCountFrequency (%)
lateness 3
33.3%
on-site 1
 
11.1%
assessment 1
 
11.1%
punctuality 1
 
11.1%
5 1
 
11.1%
home 1
 
11.1%
language 1
 
11.1%
2023-12-09T22:39:32.065653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11
15.7%
s 10
14.3%
t 7
10.0%
n 7
10.0%
a 6
 
8.6%
L 4
 
5.7%
u 3
 
4.3%
3
 
4.3%
i 2
 
2.9%
m 2
 
2.9%
Other values (14) 15
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 54
77.1%
Uppercase Letter 9
 
12.9%
Space Separator 3
 
4.3%
Other Punctuation 2
 
2.9%
Dash Punctuation 1
 
1.4%
Decimal Number 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
20.4%
s 10
18.5%
t 7
13.0%
n 7
13.0%
a 6
11.1%
u 3
 
5.6%
i 2
 
3.7%
m 2
 
3.7%
g 2
 
3.7%
c 1
 
1.9%
Other values (3) 3
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
L 4
44.4%
S 1
 
11.1%
A 1
 
11.1%
P 1
 
11.1%
O 1
 
11.1%
H 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
: 1
50.0%
% 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Decimal Number
ValueCountFrequency (%)
5 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 63
90.0%
Common 7
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
17.5%
s 10
15.9%
t 7
11.1%
n 7
11.1%
a 6
9.5%
L 4
 
6.3%
u 3
 
4.8%
i 2
 
3.2%
m 2
 
3.2%
g 2
 
3.2%
Other values (9) 9
14.3%
Common
ValueCountFrequency (%)
3
42.9%
- 1
 
14.3%
: 1
 
14.3%
5 1
 
14.3%
% 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 11
15.7%
s 10
14.3%
t 7
10.0%
n 7
10.0%
a 6
 
8.6%
L 4
 
5.7%
u 3
 
4.3%
3
 
4.3%
i 2
 
2.9%
m 2
 
2.9%
Other values (14) 15
21.4%

selectioncriteria6_prog3
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:39:32.242222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length13
Mean length13
Min length8

Characters and Unicode

Total characters26
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowLateness
2nd rowOn-Site Assessment
ValueCountFrequency (%)
lateness 1
33.3%
on-site 1
33.3%
assessment 1
33.3%
2023-12-09T22:39:32.539857image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 6
23.1%
e 5
19.2%
t 3
11.5%
n 3
11.5%
L 1
 
3.8%
a 1
 
3.8%
O 1
 
3.8%
- 1
 
3.8%
S 1
 
3.8%
i 1
 
3.8%
Other values (3) 3
11.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20
76.9%
Uppercase Letter 4
 
15.4%
Dash Punctuation 1
 
3.8%
Space Separator 1
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 6
30.0%
e 5
25.0%
t 3
15.0%
n 3
15.0%
a 1
 
5.0%
i 1
 
5.0%
m 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
25.0%
O 1
25.0%
S 1
25.0%
A 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
92.3%
Common 2
 
7.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 6
25.0%
e 5
20.8%
t 3
12.5%
n 3
12.5%
L 1
 
4.2%
a 1
 
4.2%
O 1
 
4.2%
S 1
 
4.2%
i 1
 
4.2%
A 1
 
4.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 6
23.1%
e 5
19.2%
t 3
11.5%
n 3
11.5%
L 1
 
3.8%
a 1
 
3.8%
O 1
 
3.8%
- 1
 
3.8%
S 1
 
3.8%
i 1
 
3.8%
Other values (3) 3
11.5%

selectioncriteria7_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog4
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing449
Missing (%)94.7%
Memory size15.7 KiB
2023-12-09T22:39:32.775118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.2
Min length5

Characters and Unicode

Total characters130
Distinct characters23
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st rowM324Y
2nd rowX144Y
3rd rowX180Y
4th rowX181Y
5th rowK113T
ValueCountFrequency (%)
k098da 1
 
4.0%
m324y 1
 
4.0%
k281e 1
 
4.0%
k303dr 1
 
4.0%
k180z 1
 
4.0%
x180y 1
 
4.0%
q077z 1
 
4.0%
k088y 1
 
4.0%
q093z 1
 
4.0%
q204y 1
 
4.0%
Other values (15) 15
60.0%
2023-12-09T22:39:33.127001image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
13.8%
K 12
 
9.2%
1 11
 
8.5%
2 9
 
6.9%
8 9
 
6.9%
Z 9
 
6.9%
Y 8
 
6.2%
7 7
 
5.4%
3 7
 
5.4%
Q 6
 
4.6%
Other values (13) 34
26.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
57.7%
Uppercase Letter 55
42.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 12
21.8%
Z 9
16.4%
Y 8
14.5%
Q 6
10.9%
D 4
 
7.3%
X 4
 
7.3%
R 4
 
7.3%
A 3
 
5.5%
T 1
 
1.8%
S 1
 
1.8%
Other values (3) 3
 
5.5%
Decimal Number
ValueCountFrequency (%)
0 18
24.0%
1 11
14.7%
2 9
12.0%
8 9
12.0%
7 7
 
9.3%
3 7
 
9.3%
4 6
 
8.0%
9 4
 
5.3%
6 2
 
2.7%
5 2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 75
57.7%
Latin 55
42.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 12
21.8%
Z 9
16.4%
Y 8
14.5%
Q 6
10.9%
D 4
 
7.3%
X 4
 
7.3%
R 4
 
7.3%
A 3
 
5.5%
T 1
 
1.8%
S 1
 
1.8%
Other values (3) 3
 
5.5%
Common
ValueCountFrequency (%)
0 18
24.0%
1 11
14.7%
2 9
12.0%
8 9
12.0%
7 7
 
9.3%
3 7
 
9.3%
4 6
 
8.0%
9 4
 
5.3%
6 2
 
2.7%
5 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
13.8%
K 12
 
9.2%
1 11
 
8.5%
2 9
 
6.9%
8 9
 
6.9%
Z 9
 
6.9%
Y 8
 
6.2%
7 7
 
5.4%
3 7
 
5.4%
Q 6
 
4.6%
Other values (13) 34
26.2%

name_prog4
Text

MISSING 

Distinct23
Distinct (%)92.0%
Missing449
Missing (%)94.7%
Memory size16.5 KiB
2023-12-09T22:39:33.423814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length64
Median length44
Mean length37.24
Min length13

Characters and Unicode

Total characters931
Distinct characters61
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)88.0%

Sample

1st rowPATRIA MIRABAL ACES 12:1:1 PROGRAM
2nd rowMICHELANGELO ACES 12:1:1 PROGRAM
3rd rowDR. DANIEL HALE WILLIAMS ACES 12:1:1 PROGRAM
4th rowPABLO CASALS ACES 12:1:1 PROGRAM
5th rowACATS (The Academy of Computer & Technology Science)
ValueCountFrequency (%)
program 23
 
15.9%
zoned 9
 
6.2%
aces 9
 
6.2%
i.s 9
 
6.2%
12:1:1 9
 
6.2%
the 6
 
4.1%
magnet 4
 
2.8%
academy 3
 
2.1%
school 3
 
2.1%
dance 3
 
2.1%
Other values (64) 67
46.2%
2023-12-09T22:39:33.847177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
12.9%
e 48
 
5.2%
r 42
 
4.5%
A 41
 
4.4%
o 41
 
4.4%
a 41
 
4.4%
S 35
 
3.8%
n 29
 
3.1%
. 28
 
3.0%
1 27
 
2.9%
Other values (51) 479
51.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 351
37.7%
Uppercase Letter 327
35.1%
Space Separator 120
 
12.9%
Decimal Number 60
 
6.4%
Other Punctuation 47
 
5.0%
Open Punctuation 13
 
1.4%
Close Punctuation 13
 
1.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 41
12.5%
S 35
10.7%
R 27
 
8.3%
P 27
 
8.3%
E 24
 
7.3%
I 21
 
6.4%
M 19
 
5.8%
L 19
 
5.8%
C 18
 
5.5%
O 17
 
5.2%
Other values (13) 79
24.2%
Lowercase Letter
ValueCountFrequency (%)
e 48
13.7%
r 42
12.0%
o 41
11.7%
a 41
11.7%
n 29
8.3%
m 21
 
6.0%
g 21
 
6.0%
d 18
 
5.1%
t 14
 
4.0%
c 14
 
4.0%
Other values (12) 62
17.7%
Decimal Number
ValueCountFrequency (%)
1 27
45.0%
2 12
20.0%
7 5
 
8.3%
3 5
 
8.3%
9 4
 
6.7%
5 2
 
3.3%
8 2
 
3.3%
0 1
 
1.7%
6 1
 
1.7%
4 1
 
1.7%
Other Punctuation
ValueCountFrequency (%)
. 28
59.6%
: 18
38.3%
& 1
 
2.1%
Space Separator
ValueCountFrequency (%)
120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 678
72.8%
Common 253
 
27.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 48
 
7.1%
r 42
 
6.2%
A 41
 
6.0%
o 41
 
6.0%
a 41
 
6.0%
S 35
 
5.2%
n 29
 
4.3%
R 27
 
4.0%
P 27
 
4.0%
E 24
 
3.5%
Other values (35) 323
47.6%
Common
ValueCountFrequency (%)
120
47.4%
. 28
 
11.1%
1 27
 
10.7%
: 18
 
7.1%
( 13
 
5.1%
) 13
 
5.1%
2 12
 
4.7%
7 5
 
2.0%
3 5
 
2.0%
9 4
 
1.6%
Other values (6) 8
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
 
12.9%
e 48
 
5.2%
r 42
 
4.5%
A 41
 
4.4%
o 41
 
4.4%
a 41
 
4.4%
S 35
 
3.8%
n 29
 
3.1%
. 28
 
3.0%
1 27
 
2.9%
Other values (51) 479
51.5%

admissionsmethod_prog4
Text

MISSING 

Distinct5
Distinct (%)20.0%
Missing449
Missing (%)94.7%
Memory size15.8 KiB
2023-12-09T22:39:34.045400image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length16
Mean length11.68
Min length5

Characters and Unicode

Total characters292
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st rowASD/ACES Program
2nd rowASD/ACES Program
3rd rowASD/ACES Program
4th rowASD/ACES Program
5th rowScreened
ValueCountFrequency (%)
zoned 9
20.9%
asd/aces 9
20.9%
program 9
20.9%
talent 5
11.6%
test 5
11.6%
screened 1
 
2.3%
d75 1
 
2.3%
special 1
 
2.3%
education 1
 
2.3%
inclusive 1
 
2.3%
2023-12-09T22:39:34.378390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 26
 
8.9%
S 21
 
7.2%
r 20
 
6.8%
o 19
 
6.5%
A 18
 
6.2%
18
 
6.2%
n 17
 
5.8%
a 16
 
5.5%
d 11
 
3.8%
t 11
 
3.8%
Other values (19) 115
39.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 166
56.8%
Uppercase Letter 97
33.2%
Space Separator 18
 
6.2%
Other Punctuation 9
 
3.1%
Decimal Number 2
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
15.7%
r 20
12.0%
o 19
11.4%
n 17
10.2%
a 16
9.6%
d 11
6.6%
t 11
6.6%
m 9
 
5.4%
g 9
 
5.4%
l 7
 
4.2%
Other values (6) 21
12.7%
Uppercase Letter
ValueCountFrequency (%)
S 21
21.6%
A 18
18.6%
D 10
10.3%
T 10
10.3%
E 10
10.3%
Z 9
9.3%
P 9
9.3%
C 9
9.3%
I 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
7 1
50.0%
5 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 263
90.1%
Common 29
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
 
9.9%
S 21
 
8.0%
r 20
 
7.6%
o 19
 
7.2%
A 18
 
6.8%
n 17
 
6.5%
a 16
 
6.1%
d 11
 
4.2%
t 11
 
4.2%
D 10
 
3.8%
Other values (15) 94
35.7%
Common
ValueCountFrequency (%)
18
62.1%
/ 9
31.0%
7 1
 
3.4%
5 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 292
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 26
 
8.9%
S 21
 
7.2%
r 20
 
6.8%
o 19
 
6.5%
A 18
 
6.2%
18
 
6.2%
n 17
 
5.8%
a 16
 
5.5%
d 11
 
3.8%
t 11
 
3.8%
Other values (19) 115
39.4%

geapps_prog4
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:34.588035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.866666667
Min length2

Characters and Unicode

Total characters43
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row127
2nd row74
3rd row305
4th row109
5th row199
ValueCountFrequency (%)
141 1
 
6.7%
129 1
 
6.7%
199 1
 
6.7%
584 1
 
6.7%
305 1
 
6.7%
127 1
 
6.7%
271 1
 
6.7%
109 1
 
6.7%
178 1
 
6.7%
49 1
 
6.7%
Other values (5) 5
33.3%
2023-12-09T22:39:35.482361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
27.9%
7 6
14.0%
4 5
11.6%
9 5
11.6%
2 4
 
9.3%
3 4
 
9.3%
5 2
 
4.7%
8 2
 
4.7%
0 2
 
4.7%
6 1
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 43
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
27.9%
7 6
14.0%
4 5
11.6%
9 5
11.6%
2 4
 
9.3%
3 4
 
9.3%
5 2
 
4.7%
8 2
 
4.7%
0 2
 
4.7%
6 1
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Common 43
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
27.9%
7 6
14.0%
4 5
11.6%
9 5
11.6%
2 4
 
9.3%
3 4
 
9.3%
5 2
 
4.7%
8 2
 
4.7%
0 2
 
4.7%
6 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
27.9%
7 6
14.0%
4 5
11.6%
9 5
11.6%
2 4
 
9.3%
3 4
 
9.3%
5 2
 
4.7%
8 2
 
4.7%
0 2
 
4.7%
6 1
 
2.3%

swdapps_prog4
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:35.677494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.866666667
Min length1

Characters and Unicode

Total characters28
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)73.3%

Sample

1st row26
2nd row22
3rd row45
4th row9
5th row23
ValueCountFrequency (%)
22 2
13.3%
26 2
13.3%
23 1
 
6.7%
54 1
 
6.7%
45 1
 
6.7%
46 1
 
6.7%
37 1
 
6.7%
4 1
 
6.7%
24 1
 
6.7%
9 1
 
6.7%
Other values (3) 3
20.0%
2023-12-09T22:39:35.981664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 8
28.6%
4 6
21.4%
5 4
14.3%
6 3
 
10.7%
3 3
 
10.7%
8 2
 
7.1%
7 1
 
3.6%
9 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 28
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 8
28.6%
4 6
21.4%
5 4
14.3%
6 3
 
10.7%
3 3
 
10.7%
8 2
 
7.1%
7 1
 
3.6%
9 1
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 8
28.6%
4 6
21.4%
5 4
14.3%
6 3
 
10.7%
3 3
 
10.7%
8 2
 
7.1%
7 1
 
3.6%
9 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 8
28.6%
4 6
21.4%
5 4
14.3%
6 3
 
10.7%
3 3
 
10.7%
8 2
 
7.1%
7 1
 
3.6%
9 1
 
3.6%

geappsperseat_prog4
Text

MISSING 

Distinct6
Distinct (%)40.0%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:36.096499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.133333333
Min length1

Characters and Unicode

Total characters17
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)26.7%

Sample

1st row2
2nd row1
3rd row1
4th row5
5th row7
ValueCountFrequency (%)
1 9
60.0%
2 2
 
13.3%
14 1
 
6.7%
7 1
 
6.7%
25 1
 
6.7%
5 1
 
6.7%
2023-12-09T22:39:36.329047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
58.8%
2 3
 
17.6%
5 2
 
11.8%
4 1
 
5.9%
7 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
58.8%
2 3
 
17.6%
5 2
 
11.8%
4 1
 
5.9%
7 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
58.8%
2 3
 
17.6%
5 2
 
11.8%
4 1
 
5.9%
7 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
58.8%
2 3
 
17.6%
5 2
 
11.8%
4 1
 
5.9%
7 1
 
5.9%

swdappsperseat_prog4
Text

MISSING 

Distinct6
Distinct (%)40.0%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:36.444674image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.066666667
Min length1

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)20.0%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
1 7
46.7%
2 3
20.0%
0 2
 
13.3%
10 1
 
6.7%
7 1
 
6.7%
3 1
 
6.7%
2023-12-09T22:39:36.676373image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
50.0%
2 3
 
18.8%
0 3
 
18.8%
7 1
 
6.2%
3 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
50.0%
2 3
 
18.8%
0 3
 
18.8%
7 1
 
6.2%
3 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
50.0%
2 3
 
18.8%
0 3
 
18.8%
7 1
 
6.2%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
50.0%
2 3
 
18.8%
0 3
 
18.8%
7 1
 
6.2%
3 1
 
6.2%

swdseats_prog4
Text

MISSING 

Distinct14
Distinct (%)93.3%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:36.837003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters25
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)86.7%

Sample

1st row16
2nd row11
3rd row46
4th row6
5th row8
ValueCountFrequency (%)
6 2
13.3%
33 1
 
6.7%
5 1
 
6.7%
81 1
 
6.7%
46 1
 
6.7%
71 1
 
6.7%
16 1
 
6.7%
11 1
 
6.7%
66 1
 
6.7%
53 1
 
6.7%
Other values (4) 4
26.7%
2023-12-09T22:39:37.112563image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 6
24.0%
1 5
20.0%
3 4
16.0%
5 3
12.0%
8 3
12.0%
4 3
12.0%
7 1
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 25
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 6
24.0%
1 5
20.0%
3 4
16.0%
5 3
12.0%
8 3
12.0%
4 3
12.0%
7 1
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 6
24.0%
1 5
20.0%
3 4
16.0%
5 3
12.0%
8 3
12.0%
4 3
12.0%
7 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 6
24.0%
1 5
20.0%
3 4
16.0%
5 3
12.0%
8 3
12.0%
4 3
12.0%
7 1
 
4.0%

geseats_prog4
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing459
Missing (%)96.8%
Memory size15.3 KiB
2023-12-09T22:39:37.324682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.466666667
Min length1

Characters and Unicode

Total characters37
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row69
2nd row56
3rd row242
4th row24
5th row29
ValueCountFrequency (%)
23 1
 
6.7%
282 1
 
6.7%
129 1
 
6.7%
234 1
 
6.7%
156 1
 
6.7%
29 1
 
6.7%
56 1
 
6.7%
22 1
 
6.7%
24 1
 
6.7%
242 1
 
6.7%
Other values (5) 5
33.3%
2023-12-09T22:39:37.664622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
32.4%
9 5
13.5%
6 5
13.5%
1 4
 
10.8%
3 3
 
8.1%
4 3
 
8.1%
5 2
 
5.4%
7 2
 
5.4%
8 1
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
32.4%
9 5
13.5%
6 5
13.5%
1 4
 
10.8%
3 3
 
8.1%
4 3
 
8.1%
5 2
 
5.4%
7 2
 
5.4%
8 1
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
Common 37
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
32.4%
9 5
13.5%
6 5
13.5%
1 4
 
10.8%
3 3
 
8.1%
4 3
 
8.1%
5 2
 
5.4%
7 2
 
5.4%
8 1
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
32.4%
9 5
13.5%
6 5
13.5%
1 4
 
10.8%
3 3
 
8.1%
4 3
 
8.1%
5 2
 
5.4%
7 2
 
5.4%
8 1
 
2.7%

gefilled_prog4
Text

MISSING 

Distinct2
Distinct (%)8.7%
Missing451
Missing (%)95.1%
Memory size15.5 KiB
2023-12-09T22:39:37.775456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters23
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%
2023-12-09T22:39:37.983654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

swdfilled_prog4
Text

MISSING 

Distinct2
Distinct (%)8.7%
Missing451
Missing (%)95.1%
Memory size15.5 KiB
2023-12-09T22:39:38.087203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters23
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%
2023-12-09T22:39:38.298304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20
87.0%
1 3
 
13.0%

eligibility_prog4
Text

MISSING 

Distinct7
Distinct (%)28.0%
Missing449
Missing (%)94.7%
Memory size18.2 KiB
2023-12-09T22:39:38.521087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length208
Median length201
Mean length108.56
Min length31

Characters and Unicode

Total characters2714
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)16.0%

Sample

1st rowOpen to students currently in an ACES (Academics, Career, and Essential Skills) program. If you are not currently an ACES student and are interested in the program, please contact acesprograms@schools.nyc.gov
2nd rowOpen to students currently in an ACES (Academics, Career, and Essential Skills) program. If you are not currently an ACES student and are interested in the program, please contact acesprograms@schools.nyc.gov
3rd rowOpen to students currently in an ACES (Academics, Career, and Essential Skills) program. If you are not currently an ACES student and are interested in the program, please contact acesprograms@schools.nyc.gov
4th rowOpen to students currently in an ACES (Academics, Career, and Essential Skills) program. If you are not currently an ACES student and are interested in the program, please contact acesprograms@schools.nyc.gov
5th rowOpen to students and residents of District 13
ValueCountFrequency (%)
in 29
 
7.0%
open 25
 
6.0%
students 25
 
6.0%
to 25
 
6.0%
and 24
 
5.8%
currently 20
 
4.8%
are 19
 
4.6%
an 18
 
4.3%
aces 18
 
4.3%
the 18
 
4.3%
Other values (38) 193
46.6%
2023-12-09T22:39:38.892867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389
14.3%
e 257
 
9.5%
n 231
 
8.5%
t 212
 
7.8%
s 185
 
6.8%
r 172
 
6.3%
a 148
 
5.5%
o 138
 
5.1%
i 110
 
4.1%
c 102
 
3.8%
Other values (32) 770
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2066
76.1%
Space Separator 389
 
14.3%
Uppercase Letter 157
 
5.8%
Other Punctuation 69
 
2.5%
Decimal Number 15
 
0.6%
Close Punctuation 9
 
0.3%
Open Punctuation 9
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 257
12.4%
n 231
11.2%
t 212
10.3%
s 185
9.0%
r 172
8.3%
a 148
 
7.2%
o 138
 
6.7%
i 110
 
5.3%
c 102
 
4.9%
d 97
 
4.7%
Other values (12) 414
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 29
18.5%
C 28
17.8%
E 28
17.8%
A 27
17.2%
O 25
15.9%
I 11
 
7.0%
D 7
 
4.5%
N 1
 
0.6%
Y 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 5
33.3%
2 4
26.7%
5 3
20.0%
7 2
 
13.3%
3 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 31
44.9%
, 28
40.6%
@ 10
 
14.5%
Space Separator
ValueCountFrequency (%)
389
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2223
81.9%
Common 491
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 257
11.6%
n 231
10.4%
t 212
 
9.5%
s 185
 
8.3%
r 172
 
7.7%
a 148
 
6.7%
o 138
 
6.2%
i 110
 
4.9%
c 102
 
4.6%
d 97
 
4.4%
Other values (21) 571
25.7%
Common
ValueCountFrequency (%)
389
79.2%
. 31
 
6.3%
, 28
 
5.7%
@ 10
 
2.0%
) 9
 
1.8%
( 9
 
1.8%
1 5
 
1.0%
2 4
 
0.8%
5 3
 
0.6%
7 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
389
14.3%
e 257
 
9.5%
n 231
 
8.5%
t 212
 
7.8%
s 185
 
6.8%
r 172
 
6.3%
a 148
 
5.5%
o 138
 
5.1%
i 110
 
4.1%
c 102
 
3.8%
Other values (32) 770
28.4%

priority1_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:39.074236image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters31
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to continuing students
ValueCountFrequency (%)
priority 1
25.0%
to 1
25.0%
continuing 1
25.0%
students 1
25.0%
2023-12-09T22:39:39.371307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 5
16.1%
i 4
12.9%
n 4
12.9%
o 3
9.7%
3
9.7%
r 2
 
6.5%
u 2
 
6.5%
s 2
 
6.5%
P 1
 
3.2%
y 1
 
3.2%
Other values (4) 4
12.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
87.1%
Space Separator 3
 
9.7%
Uppercase Letter 1
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 5
18.5%
i 4
14.8%
n 4
14.8%
o 3
11.1%
r 2
 
7.4%
u 2
 
7.4%
s 2
 
7.4%
y 1
 
3.7%
c 1
 
3.7%
g 1
 
3.7%
Other values (2) 2
 
7.4%
Space Separator
ValueCountFrequency (%)
3
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
90.3%
Common 3
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 5
17.9%
i 4
14.3%
n 4
14.3%
o 3
10.7%
r 2
 
7.1%
u 2
 
7.1%
s 2
 
7.1%
P 1
 
3.6%
y 1
 
3.6%
c 1
 
3.6%
Other values (3) 3
10.7%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 31
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 5
16.1%
i 4
12.9%
n 4
12.9%
o 3
9.7%
3
9.7%
r 2
 
6.5%
u 2
 
6.5%
s 2
 
6.5%
P 1
 
3.2%
y 1
 
3.2%
Other values (4) 4
12.9%

priority2_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:39.564164image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to residents of the elementary school zone
ValueCountFrequency (%)
then 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
elementary 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:39:39.878886image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 8
17.0%
7
14.9%
o 5
10.6%
n 4
8.5%
t 4
8.5%
s 3
 
6.4%
h 3
 
6.4%
r 2
 
4.3%
l 2
 
4.3%
T 1
 
2.1%
Other values (8) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8
20.5%
o 5
12.8%
n 4
10.3%
t 4
10.3%
s 3
 
7.7%
h 3
 
7.7%
r 2
 
5.1%
l 2
 
5.1%
a 1
 
2.6%
c 1
 
2.6%
Other values (6) 6
15.4%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8
20.0%
o 5
12.5%
n 4
10.0%
t 4
10.0%
s 3
 
7.5%
h 3
 
7.5%
r 2
 
5.0%
l 2
 
5.0%
T 1
 
2.5%
a 1
 
2.5%
Other values (7) 7
17.5%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8
17.0%
7
14.9%
o 5
10.6%
n 4
8.5%
t 4
8.5%
s 3
 
6.4%
h 3
 
6.4%
r 2
 
4.3%
l 2
 
4.3%
T 1
 
2.1%
Other values (8) 8
17.0%

priority3_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

prefnote_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog4
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.7 KiB
2023-12-09T22:39:40.098965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length106
Mean length97.33333333
Min length43

Characters and Unicode

Total characters584
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st row4th Grade New York State ELA and Math Exams
2nd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
3rd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
4th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
5th rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
ValueCountFrequency (%)
on 10
 
9.5%
students 5
 
4.8%
based 5
 
4.8%
21 5
 
4.8%
who 5
 
4.8%
the 5
 
4.8%
score 5
 
4.8%
their 5
 
4.8%
selected 5
 
4.8%
tests 5
 
4.8%
Other values (19) 50
47.6%
2023-12-09T22:39:40.466022image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
17.0%
e 68
11.6%
t 59
 
10.1%
s 46
 
7.9%
o 31
 
5.3%
r 28
 
4.8%
a 27
 
4.6%
l 25
 
4.3%
n 22
 
3.8%
h 22
 
3.8%
Other values (26) 157
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 442
75.7%
Space Separator 99
 
17.0%
Uppercase Letter 31
 
5.3%
Decimal Number 11
 
1.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68
15.4%
t 59
13.3%
s 46
10.4%
o 31
 
7.0%
r 28
 
6.3%
a 27
 
6.1%
l 25
 
5.7%
n 22
 
5.0%
h 22
 
5.0%
i 21
 
4.8%
Other values (11) 93
21.0%
Uppercase Letter
ValueCountFrequency (%)
T 11
35.5%
S 6
19.4%
D 5
16.1%
M 2
 
6.5%
E 2
 
6.5%
Y 1
 
3.2%
A 1
 
3.2%
L 1
 
3.2%
N 1
 
3.2%
G 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 5
45.5%
4 1
 
9.1%
Space Separator
ValueCountFrequency (%)
99
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 473
81.0%
Common 111
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68
14.4%
t 59
12.5%
s 46
 
9.7%
o 31
 
6.6%
r 28
 
5.9%
a 27
 
5.7%
l 25
 
5.3%
n 22
 
4.7%
h 22
 
4.7%
i 21
 
4.4%
Other values (21) 124
26.2%
Common
ValueCountFrequency (%)
99
89.2%
2 5
 
4.5%
1 5
 
4.5%
/ 1
 
0.9%
4 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
17.0%
e 68
11.6%
t 59
 
10.1%
s 46
 
7.9%
o 31
 
5.3%
r 28
 
4.8%
a 27
 
4.6%
l 25
 
4.3%
n 22
 
3.8%
h 22
 
3.8%
Other values (26) 157
26.9%

selectioncriteria2_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:40.634707image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAttendance
ValueCountFrequency (%)
attendance 1
100.0%
2023-12-09T22:39:40.897583image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
90.0%
Uppercase Letter 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2
22.2%
e 2
22.2%
n 2
22.2%
d 1
11.1%
a 1
11.1%
c 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

selectioncriteria3_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:41.067901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters27
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowFinal 4th Grade Report Card
ValueCountFrequency (%)
final 1
20.0%
4th 1
20.0%
grade 1
20.0%
report 1
20.0%
card 1
20.0%
2023-12-09T22:39:41.369360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
66.7%
Space Separator 4
 
14.8%
Uppercase Letter 4
 
14.8%
Decimal Number 1
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
a 3
16.7%
t 2
11.1%
e 2
11.1%
d 2
11.1%
o 1
 
5.6%
p 1
 
5.6%
h 1
 
5.6%
i 1
 
5.6%
l 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
F 1
25.0%
R 1
25.0%
G 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22
81.5%
Common 5
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 3
13.6%
a 3
13.6%
t 2
 
9.1%
e 2
 
9.1%
d 2
 
9.1%
F 1
 
4.5%
o 1
 
4.5%
p 1
 
4.5%
R 1
 
4.5%
h 1
 
4.5%
Other values (5) 5
22.7%
Common
ValueCountFrequency (%)
4
80.0%
4 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

selectioncriteria4_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:41.521311image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLateness
ValueCountFrequency (%)
lateness 1
100.0%
2023-12-09T22:39:41.779457image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
s 2
28.6%
a 1
14.3%
t 1
14.3%
n 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

selectioncriteria5_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:41.948767image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length55
Median length55
Mean length55
Min length55

Characters and Unicode

Total characters55
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowMath and English Assessment - Multiple choice and Essay
ValueCountFrequency (%)
and 2
22.2%
math 1
11.1%
english 1
11.1%
assessment 1
11.1%
1
11.1%
multiple 1
11.1%
choice 1
11.1%
essay 1
11.1%
2023-12-09T22:39:42.235989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
14.5%
s 7
12.7%
a 4
 
7.3%
n 4
 
7.3%
e 4
 
7.3%
i 3
 
5.5%
t 3
 
5.5%
h 3
 
5.5%
l 3
 
5.5%
c 2
 
3.6%
Other values (11) 14
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41
74.5%
Space Separator 8
 
14.5%
Uppercase Letter 5
 
9.1%
Dash Punctuation 1
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 7
17.1%
a 4
9.8%
n 4
9.8%
e 4
9.8%
i 3
7.3%
t 3
7.3%
h 3
7.3%
l 3
7.3%
c 2
 
4.9%
d 2
 
4.9%
Other values (6) 6
14.6%
Uppercase Letter
ValueCountFrequency (%)
M 2
40.0%
E 2
40.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
83.6%
Common 9
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 7
15.2%
a 4
 
8.7%
n 4
 
8.7%
e 4
 
8.7%
i 3
 
6.5%
t 3
 
6.5%
h 3
 
6.5%
l 3
 
6.5%
c 2
 
4.3%
M 2
 
4.3%
Other values (9) 11
23.9%
Common
ValueCountFrequency (%)
8
88.9%
- 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
14.5%
s 7
12.7%
a 4
 
7.3%
n 4
 
7.3%
e 4
 
7.3%
i 3
 
5.5%
t 3
 
5.5%
h 3
 
5.5%
l 3
 
5.5%
c 2
 
3.6%
Other values (11) 14
25.5%

selectioncriteria6_prog4
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:42.404268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOn-Site Assessment
ValueCountFrequency (%)
on-site 1
50.0%
assessment 1
50.0%
2023-12-09T22:39:42.681280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
72.2%
Uppercase Letter 3
 
16.7%
Dash Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 3
23.1%
n 2
15.4%
t 2
15.4%
i 1
 
7.7%
m 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
S 1
33.3%
A 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
25.0%
e 3
18.8%
n 2
12.5%
t 2
12.5%
O 1
 
6.2%
S 1
 
6.2%
i 1
 
6.2%
A 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

selectioncriteria7_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog5
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing463
Missing (%)97.7%
Memory size15.3 KiB
2023-12-09T22:39:42.876800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.454545455
Min length5

Characters and Unicode

Total characters60
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowX144Z
2nd rowX181Z
3rd rowK096ST
4th rowK098DR
5th rowK228DR
ValueCountFrequency (%)
k098dr 1
9.1%
k303e 1
9.1%
k014y 1
9.1%
k281jo 1
9.1%
k096st 1
9.1%
q204z 1
9.1%
k239dr 1
9.1%
x144z 1
9.1%
x181z 1
9.1%
r075z 1
9.1%
2023-12-09T22:39:43.191984image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 7
11.7%
0 6
 
10.0%
1 5
 
8.3%
2 5
 
8.3%
8 4
 
6.7%
4 4
 
6.7%
Z 4
 
6.7%
R 4
 
6.7%
D 3
 
5.0%
3 3
 
5.0%
Other values (12) 15
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33
55.0%
Uppercase Letter 27
45.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 7
25.9%
Z 4
14.8%
R 4
14.8%
D 3
11.1%
X 2
 
7.4%
T 1
 
3.7%
Q 1
 
3.7%
O 1
 
3.7%
S 1
 
3.7%
J 1
 
3.7%
Other values (2) 2
 
7.4%
Decimal Number
ValueCountFrequency (%)
0 6
18.2%
1 5
15.2%
2 5
15.2%
8 4
12.1%
4 4
12.1%
3 3
9.1%
9 3
9.1%
7 1
 
3.0%
6 1
 
3.0%
5 1
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33
55.0%
Latin 27
45.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 7
25.9%
Z 4
14.8%
R 4
14.8%
D 3
11.1%
X 2
 
7.4%
T 1
 
3.7%
Q 1
 
3.7%
O 1
 
3.7%
S 1
 
3.7%
J 1
 
3.7%
Other values (2) 2
 
7.4%
Common
ValueCountFrequency (%)
0 6
18.2%
1 5
15.2%
2 5
15.2%
8 4
12.1%
4 4
12.1%
3 3
9.1%
9 3
9.1%
7 1
 
3.0%
6 1
 
3.0%
5 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 7
11.7%
0 6
 
10.0%
1 5
 
8.3%
2 5
 
8.3%
8 4
 
6.7%
4 4
 
6.7%
Z 4
 
6.7%
R 4
 
6.7%
D 3
 
5.0%
3 3
 
5.0%
Other values (12) 15
25.0%

name_prog5
Text

MISSING 

Distinct10
Distinct (%)90.9%
Missing463
Missing (%)97.7%
Memory size15.6 KiB
2023-12-09T22:39:43.438280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length49
Mean length41
Min length13

Characters and Unicode

Total characters451
Distinct characters53
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)81.8%

Sample

1st rowZoned Program
2nd rowPablo Casals (I.S. 181)
3rd rowSeth Low (I.S. 96) Magnet Program (Instrumental-Strings)
4th rowThe Bay Academy (I.S. 98) Magnet Program (Drama)
5th rowDavid A. Boody (I.S. 228) Magnet Program (Drama)
ValueCountFrequency (%)
program 9
 
13.2%
i.s 7
 
10.3%
magnet 4
 
5.9%
zoned 3
 
4.4%
drama 3
 
4.4%
the 2
 
2.9%
school 2
 
2.9%
228 1
 
1.5%
eisenberg 1
 
1.5%
horizon 1
 
1.5%
Other values (35) 35
51.5%
2023-12-09T22:39:43.815941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57
 
12.6%
a 34
 
7.5%
r 34
 
7.5%
o 28
 
6.2%
e 24
 
5.3%
n 20
 
4.4%
. 17
 
3.8%
g 17
 
3.8%
m 16
 
3.5%
l 15
 
3.3%
Other values (43) 189
41.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 260
57.6%
Uppercase Letter 72
 
16.0%
Space Separator 57
 
12.6%
Decimal Number 21
 
4.7%
Other Punctuation 18
 
4.0%
Close Punctuation 11
 
2.4%
Open Punctuation 11
 
2.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 34
13.1%
r 34
13.1%
o 28
10.8%
e 24
9.2%
n 20
7.7%
g 17
 
6.5%
m 16
 
6.2%
l 15
 
5.8%
i 13
 
5.0%
t 11
 
4.2%
Other values (12) 48
18.5%
Uppercase Letter
ValueCountFrequency (%)
S 14
19.4%
P 10
13.9%
I 9
12.5%
D 6
8.3%
M 5
 
6.9%
B 4
 
5.6%
H 4
 
5.6%
T 3
 
4.2%
Z 3
 
4.2%
J 3
 
4.2%
Other values (6) 11
15.3%
Decimal Number
ValueCountFrequency (%)
8 4
19.0%
2 4
19.0%
9 3
14.3%
3 3
14.3%
1 3
14.3%
0 1
 
4.8%
7 1
 
4.8%
5 1
 
4.8%
6 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 17
94.4%
/ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 332
73.6%
Common 119
 
26.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 34
 
10.2%
r 34
 
10.2%
o 28
 
8.4%
e 24
 
7.2%
n 20
 
6.0%
g 17
 
5.1%
m 16
 
4.8%
l 15
 
4.5%
S 14
 
4.2%
i 13
 
3.9%
Other values (28) 117
35.2%
Common
ValueCountFrequency (%)
57
47.9%
. 17
 
14.3%
) 11
 
9.2%
( 11
 
9.2%
8 4
 
3.4%
2 4
 
3.4%
9 3
 
2.5%
3 3
 
2.5%
1 3
 
2.5%
/ 1
 
0.8%
Other values (5) 5
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 451
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57
 
12.6%
a 34
 
7.5%
r 34
 
7.5%
o 28
 
6.2%
e 24
 
5.3%
n 20
 
4.4%
. 17
 
3.8%
g 17
 
3.8%
m 16
 
3.5%
l 15
 
3.3%
Other values (43) 189
41.9%

admissionsmethod_prog5
Text

MISSING 

Distinct4
Distinct (%)36.4%
Missing463
Missing (%)97.7%
Memory size15.3 KiB
2023-12-09T22:39:44.005464image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length16
Mean length11.90909091
Min length5

Characters and Unicode

Total characters131
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st rowZoned
2nd rowZoned
3rd rowTalent Test
4th rowTalent Test
5th rowTalent Test
ValueCountFrequency (%)
talent 5
23.8%
test 5
23.8%
zoned 4
19.0%
d75 1
 
4.8%
special 1
 
4.8%
education 1
 
4.8%
inclusive 1
 
4.8%
services 1
 
4.8%
asd/aces 1
 
4.8%
program 1
 
4.8%
2023-12-09T22:39:44.311046image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 18
13.7%
n 11
 
8.4%
t 11
 
8.4%
T 10
 
7.6%
10
 
7.6%
a 8
 
6.1%
l 7
 
5.3%
s 7
 
5.3%
o 6
 
4.6%
d 5
 
3.8%
Other values (19) 38
29.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 91
69.5%
Uppercase Letter 27
 
20.6%
Space Separator 10
 
7.6%
Decimal Number 2
 
1.5%
Other Punctuation 1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 18
19.8%
n 11
12.1%
t 11
12.1%
a 8
8.8%
l 7
 
7.7%
s 7
 
7.7%
o 6
 
6.6%
d 5
 
5.5%
i 4
 
4.4%
c 4
 
4.4%
Other values (6) 10
11.0%
Uppercase Letter
ValueCountFrequency (%)
T 10
37.0%
S 4
 
14.8%
Z 4
 
14.8%
D 2
 
7.4%
E 2
 
7.4%
A 2
 
7.4%
I 1
 
3.7%
C 1
 
3.7%
P 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
7 1
50.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 118
90.1%
Common 13
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 18
15.3%
n 11
 
9.3%
t 11
 
9.3%
T 10
 
8.5%
a 8
 
6.8%
l 7
 
5.9%
s 7
 
5.9%
o 6
 
5.1%
d 5
 
4.2%
i 4
 
3.4%
Other values (15) 31
26.3%
Common
ValueCountFrequency (%)
10
76.9%
5 1
 
7.7%
7 1
 
7.7%
/ 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 131
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 18
13.7%
n 11
 
8.4%
t 11
 
8.4%
T 10
 
7.6%
10
 
7.6%
a 8
 
6.1%
l 7
 
5.3%
s 7
 
5.3%
o 6
 
4.6%
d 5
 
3.8%
Other values (19) 38
29.0%

geapps_prog5
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:44.507487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.555555556
Min length2

Characters and Unicode

Total characters23
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row55
2nd row31
3rd row11
4th row192
5th row146
ValueCountFrequency (%)
55 1
11.1%
156 1
11.1%
271 1
11.1%
31 1
11.1%
11 1
11.1%
53 1
11.1%
146 1
11.1%
192 1
11.1%
580 1
11.1%
2023-12-09T22:39:44.819631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7
30.4%
5 5
21.7%
6 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
0 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7
30.4%
5 5
21.7%
6 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
0 1
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 23
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7
30.4%
5 5
21.7%
6 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
0 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7
30.4%
5 5
21.7%
6 2
 
8.7%
2 2
 
8.7%
3 2
 
8.7%
7 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
8 1
 
4.3%
0 1
 
4.3%

swdapps_prog5
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:45.005739image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters15
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row11
2nd row6
3rd row1
4th row14
5th row19
ValueCountFrequency (%)
63 1
11.1%
1 1
11.1%
45 1
11.1%
14 1
11.1%
10 1
11.1%
7 1
11.1%
6 1
11.1%
11 1
11.1%
19 1
11.1%
2023-12-09T22:39:45.309330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
40.0%
6 2
 
13.3%
4 2
 
13.3%
3 1
 
6.7%
5 1
 
6.7%
0 1
 
6.7%
7 1
 
6.7%
9 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
40.0%
6 2
 
13.3%
4 2
 
13.3%
3 1
 
6.7%
5 1
 
6.7%
0 1
 
6.7%
7 1
 
6.7%
9 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
40.0%
6 2
 
13.3%
4 2
 
13.3%
3 1
 
6.7%
5 1
 
6.7%
0 1
 
6.7%
7 1
 
6.7%
9 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
40.0%
6 2
 
13.3%
4 2
 
13.3%
3 1
 
6.7%
5 1
 
6.7%
0 1
 
6.7%
7 1
 
6.7%
9 1
 
6.7%

geappsperseat_prog5
Text

MISSING 

Distinct5
Distinct (%)55.6%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:45.423154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.222222222
Min length1

Characters and Unicode

Total characters11
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)44.4%

Sample

1st row1
2nd row1
3rd row1
4th row7
5th row18
ValueCountFrequency (%)
1 5
55.6%
23 1
 
11.1%
7 1
 
11.1%
18 1
 
11.1%
8 1
 
11.1%
2023-12-09T22:39:45.652629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
54.5%
8 2
 
18.2%
2 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
54.5%
8 2
 
18.2%
2 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
54.5%
8 2
 
18.2%
2 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
54.5%
8 2
 
18.2%
2 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

swdappsperseat_prog5
Text

MISSING 

Distinct4
Distinct (%)44.4%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:45.761439image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.222222222
Min length1

Characters and Unicode

Total characters11
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)33.3%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row10
ValueCountFrequency (%)
1 6
66.7%
10 1
 
11.1%
15 1
 
11.1%
2 1
 
11.1%
2023-12-09T22:39:45.990173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
72.7%
0 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
72.7%
0 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
72.7%
0 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
72.7%
0 1
 
9.1%
5 1
 
9.1%
2 1
 
9.1%

swdseats_prog5
Text

MISSING 

Distinct6
Distinct (%)66.7%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:46.123352image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters12
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)44.4%

Sample

1st row14
2nd row7
3rd row2
4th row7
5th row2
ValueCountFrequency (%)
7 3
33.3%
2 2
22.2%
5 1
 
11.1%
14 1
 
11.1%
102 1
 
11.1%
3 1
 
11.1%
2023-12-09T22:39:46.401361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 3
25.0%
2 3
25.0%
1 2
16.7%
5 1
 
8.3%
4 1
 
8.3%
0 1
 
8.3%
3 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 3
25.0%
2 3
25.0%
1 2
16.7%
5 1
 
8.3%
4 1
 
8.3%
0 1
 
8.3%
3 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 3
25.0%
2 3
25.0%
1 2
16.7%
5 1
 
8.3%
4 1
 
8.3%
0 1
 
8.3%
3 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 3
25.0%
2 3
25.0%
1 2
16.7%
5 1
 
8.3%
4 1
 
8.3%
0 1
 
8.3%
3 1
 
8.3%

geseats_prog5
Text

MISSING 

Distinct8
Distinct (%)88.9%
Missing465
Missing (%)98.1%
Memory size15.2 KiB
2023-12-09T22:39:46.559944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.888888889
Min length1

Characters and Unicode

Total characters17
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)77.8%

Sample

1st row57
2nd row26
3rd row8
4th row29
5th row8
ValueCountFrequency (%)
8 2
22.2%
300 1
11.1%
42 1
11.1%
25 1
11.1%
29 1
11.1%
57 1
11.1%
26 1
11.1%
20 1
11.1%
2023-12-09T22:39:46.866250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5
29.4%
0 3
17.6%
8 2
 
11.8%
5 2
 
11.8%
3 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
7 1
 
5.9%
6 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5
29.4%
0 3
17.6%
8 2
 
11.8%
5 2
 
11.8%
3 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
7 1
 
5.9%
6 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5
29.4%
0 3
17.6%
8 2
 
11.8%
5 2
 
11.8%
3 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
7 1
 
5.9%
6 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5
29.4%
0 3
17.6%
8 2
 
11.8%
5 2
 
11.8%
3 1
 
5.9%
4 1
 
5.9%
9 1
 
5.9%
7 1
 
5.9%
6 1
 
5.9%

gefilled_prog5
Text

MISSING 

Distinct2
Distinct (%)20.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:39:46.977745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%
2023-12-09T22:39:47.192159image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6
60.0%
1 4
40.0%

swdfilled_prog5
Text

MISSING 

Distinct2
Distinct (%)20.0%
Missing464
Missing (%)97.9%
Memory size15.2 KiB
2023-12-09T22:39:47.301141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters10
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)10.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 9
90.0%
1 1
 
10.0%
2023-12-09T22:39:47.511752image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
90.0%
1 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
90.0%
1 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
90.0%
1 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
90.0%
1 1
 
10.0%

eligibility_prog5
Text

MISSING 

Distinct6
Distinct (%)54.5%
Missing463
Missing (%)97.7%
Memory size16.0 KiB
2023-12-09T22:39:47.742145image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length206
Median length201
Mean length69.72727273
Min length31

Characters and Unicode

Total characters767
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)36.4%

Sample

1st rowOpen to students residing in the zone.
2nd rowOpen to students residing in the zone
3rd rowOpen to students and residents of District 21
4th rowOpen to students and residents of District 21
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 11
 
8.9%
to 11
 
8.9%
students 10
 
8.1%
in 8
 
6.5%
district 5
 
4.0%
the 5
 
4.0%
residents 5
 
4.0%
and 5
 
4.0%
of 4
 
3.2%
21 4
 
3.2%
Other values (32) 56
45.2%
2023-12-09T22:39:48.105118image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
14.7%
e 76
9.9%
t 70
 
9.1%
n 68
 
8.9%
s 56
 
7.3%
o 48
 
6.3%
r 46
 
6.0%
i 43
 
5.6%
d 33
 
4.3%
c 25
 
3.3%
Other values (32) 189
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 591
77.1%
Space Separator 113
 
14.7%
Uppercase Letter 37
 
4.8%
Other Punctuation 12
 
1.6%
Decimal Number 12
 
1.6%
Close Punctuation 1
 
0.1%
Open Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 76
12.9%
t 70
11.8%
n 68
11.5%
s 56
9.5%
o 48
8.1%
r 46
7.8%
i 43
7.3%
d 33
 
5.6%
c 25
 
4.2%
u 21
 
3.6%
Other values (12) 105
17.8%
Uppercase Letter
ValueCountFrequency (%)
O 11
29.7%
D 9
24.3%
S 5
13.5%
I 3
 
8.1%
A 3
 
8.1%
H 2
 
5.4%
E 1
 
2.7%
N 1
 
2.7%
Y 1
 
2.7%
C 1
 
2.7%
Decimal Number
ValueCountFrequency (%)
2 4
33.3%
1 4
33.3%
5 2
16.7%
7 2
16.7%
Other Punctuation
ValueCountFrequency (%)
. 8
66.7%
@ 2
 
16.7%
, 2
 
16.7%
Space Separator
ValueCountFrequency (%)
113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 628
81.9%
Common 139
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 76
12.1%
t 70
11.1%
n 68
10.8%
s 56
 
8.9%
o 48
 
7.6%
r 46
 
7.3%
i 43
 
6.8%
d 33
 
5.3%
c 25
 
4.0%
u 21
 
3.3%
Other values (22) 142
22.6%
Common
ValueCountFrequency (%)
113
81.3%
. 8
 
5.8%
2 4
 
2.9%
1 4
 
2.9%
5 2
 
1.4%
@ 2
 
1.4%
7 2
 
1.4%
, 2
 
1.4%
) 1
 
0.7%
( 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 767
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
14.7%
e 76
9.9%
t 70
 
9.1%
n 68
 
8.9%
s 56
 
7.3%
o 48
 
6.3%
r 46
 
6.0%
i 43
 
5.6%
d 33
 
4.3%
c 25
 
3.3%
Other values (32) 189
24.6%

priority1_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

prefnote_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog5
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.6 KiB
2023-12-09T22:39:48.328108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length106
Mean length108.2
Min length106

Characters and Unicode

Total characters541
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
3rd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
4th rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
5th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 10
 
10.4%
based 5
 
5.2%
tests 5
 
5.2%
talent 5
 
5.2%
21 5
 
5.2%
the 5
 
5.2%
score 5
 
5.2%
their 5
 
5.2%
who 5
 
5.2%
students 5
 
5.2%
Other values (10) 41
42.7%
2023-12-09T22:39:48.641383image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
16.8%
e 65
12.0%
t 55
 
10.2%
s 45
 
8.3%
o 30
 
5.5%
r 26
 
4.8%
l 25
 
4.6%
a 22
 
4.1%
i 21
 
3.9%
n 21
 
3.9%
Other values (18) 140
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 417
77.1%
Space Separator 91
 
16.8%
Uppercase Letter 22
 
4.1%
Decimal Number 10
 
1.8%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 65
15.6%
t 55
13.2%
s 45
10.8%
o 30
 
7.2%
r 26
 
6.2%
l 25
 
6.0%
a 22
 
5.3%
i 21
 
5.0%
n 21
 
5.0%
h 20
 
4.8%
Other values (10) 87
20.9%
Uppercase Letter
ValueCountFrequency (%)
T 11
50.0%
D 5
22.7%
S 5
22.7%
M 1
 
4.5%
Decimal Number
ValueCountFrequency (%)
1 5
50.0%
2 5
50.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 439
81.1%
Common 102
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 65
14.8%
t 55
12.5%
s 45
10.3%
o 30
 
6.8%
r 26
 
5.9%
l 25
 
5.7%
a 22
 
5.0%
i 21
 
4.8%
n 21
 
4.8%
h 20
 
4.6%
Other values (14) 109
24.8%
Common
ValueCountFrequency (%)
91
89.2%
1 5
 
4.9%
2 5
 
4.9%
/ 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
16.8%
e 65
12.0%
t 55
 
10.2%
s 45
 
8.3%
o 30
 
5.5%
r 26
 
4.8%
l 25
 
4.6%
a 22
 
4.1%
i 21
 
3.9%
n 21
 
3.9%
Other values (18) 140
25.9%

selectioncriteria2_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:48.827717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.666666667
Min length5

Characters and Unicode

Total characters34
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096U
2nd rowK098JO
3rd rowK228JO
4th rowK239JO
5th rowK281M
ValueCountFrequency (%)
k239jo 1
16.7%
k281m 1
16.7%
k098jo 1
16.7%
k096u 1
16.7%
k303jo 1
16.7%
k228jo 1
16.7%
2023-12-09T22:39:49.124337image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
17.6%
2 4
11.8%
J 4
11.8%
O 4
11.8%
3 3
8.8%
9 3
8.8%
8 3
8.8%
0 3
8.8%
1 1
 
2.9%
M 1
 
2.9%
Other values (2) 2
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
52.9%
Uppercase Letter 16
47.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
22.2%
3 3
16.7%
9 3
16.7%
8 3
16.7%
0 3
16.7%
1 1
 
5.6%
6 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
K 6
37.5%
J 4
25.0%
O 4
25.0%
M 1
 
6.2%
U 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 18
52.9%
Latin 16
47.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
22.2%
3 3
16.7%
9 3
16.7%
8 3
16.7%
0 3
16.7%
1 1
 
5.6%
6 1
 
5.6%
Latin
ValueCountFrequency (%)
K 6
37.5%
J 4
25.0%
O 4
25.0%
M 1
 
6.2%
U 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 34
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
17.6%
2 4
11.8%
J 4
11.8%
O 4
11.8%
3 3
8.8%
9 3
8.8%
8 3
8.8%
0 3
8.8%
1 1
 
2.9%
M 1
 
2.9%
Other values (2) 2
 
5.9%

name_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.4 KiB
2023-12-09T22:39:49.349660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length76
Median length65.5
Mean length57.66666667
Min length18

Characters and Unicode

Total characters346
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSeth Low (I.S. 96)
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Creative Writing/Journalism)
3rd rowDavid A. Boody (I.S. 228) Magnet Program (Creative Writing/Journalism)
4th rowMark Twain (I.S. 239) (Creative Writing/Journalism)
5th rowJoseph B. Cavallaro (I.S. 281) Mandarin Dual Language Program
ValueCountFrequency (%)
i.s 6
 
13.0%
writing/journalism 4
 
8.7%
program 4
 
8.7%
creative 4
 
8.7%
magnet 3
 
6.5%
mandarin 1
 
2.2%
joseph 1
 
2.2%
b 1
 
2.2%
cavallaro 1
 
2.2%
281 1
 
2.2%
Other values (20) 20
43.5%
2023-12-09T22:39:49.702896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
11.6%
a 28
 
8.1%
r 26
 
7.5%
i 20
 
5.8%
e 20
 
5.8%
n 16
 
4.6%
. 15
 
4.3%
g 14
 
4.0%
t 13
 
3.8%
o 13
 
3.8%
Other values (37) 141
40.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 201
58.1%
Uppercase Letter 50
 
14.5%
Space Separator 40
 
11.6%
Other Punctuation 19
 
5.5%
Decimal Number 16
 
4.6%
Open Punctuation 10
 
2.9%
Close Punctuation 10
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 28
13.9%
r 26
12.9%
i 20
10.0%
e 20
10.0%
n 16
8.0%
g 14
 
7.0%
t 13
 
6.5%
o 13
 
6.5%
m 9
 
4.5%
l 7
 
3.5%
Other values (11) 35
17.4%
Uppercase Letter
ValueCountFrequency (%)
S 8
16.0%
I 6
12.0%
C 5
10.0%
M 5
10.0%
J 5
10.0%
W 4
8.0%
P 4
8.0%
B 3
 
6.0%
L 2
 
4.0%
D 2
 
4.0%
Other values (4) 6
12.0%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
3 3
18.8%
8 3
18.8%
9 3
18.8%
6 1
 
6.2%
0 1
 
6.2%
1 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 15
78.9%
/ 4
 
21.1%
Space Separator
ValueCountFrequency (%)
40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 251
72.5%
Common 95
 
27.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 28
 
11.2%
r 26
 
10.4%
i 20
 
8.0%
e 20
 
8.0%
n 16
 
6.4%
g 14
 
5.6%
t 13
 
5.2%
o 13
 
5.2%
m 9
 
3.6%
S 8
 
3.2%
Other values (25) 84
33.5%
Common
ValueCountFrequency (%)
40
42.1%
. 15
 
15.8%
( 10
 
10.5%
) 10
 
10.5%
2 4
 
4.2%
/ 4
 
4.2%
3 3
 
3.2%
8 3
 
3.2%
9 3
 
3.2%
6 1
 
1.1%
Other values (2) 2
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 346
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40
 
11.6%
a 28
 
8.1%
r 26
 
7.5%
i 20
 
5.8%
e 20
 
5.8%
n 16
 
4.6%
. 15
 
4.3%
g 14
 
4.0%
t 13
 
3.8%
o 13
 
3.8%
Other values (37) 141
40.8%

admissionsmethod_prog6
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:49.879128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11
Min length4

Characters and Unicode

Total characters66
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowOpen
2nd rowTalent Test
3rd rowTalent Test
4th rowTalent Test
5th rowScreened: Language
ValueCountFrequency (%)
talent 4
36.4%
test 4
36.4%
open 1
 
9.1%
screened 1
 
9.1%
language 1
 
9.1%
2023-12-09T22:39:50.178599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 13
19.7%
T 8
12.1%
t 8
12.1%
n 7
10.6%
a 6
9.1%
5
 
7.6%
l 4
 
6.1%
s 4
 
6.1%
g 2
 
3.0%
d 1
 
1.5%
Other values (8) 8
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 49
74.2%
Uppercase Letter 11
 
16.7%
Space Separator 5
 
7.6%
Other Punctuation 1
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
26.5%
t 8
16.3%
n 7
14.3%
a 6
12.2%
l 4
 
8.2%
s 4
 
8.2%
g 2
 
4.1%
d 1
 
2.0%
p 1
 
2.0%
r 1
 
2.0%
Other values (2) 2
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
T 8
72.7%
L 1
 
9.1%
S 1
 
9.1%
O 1
 
9.1%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 60
90.9%
Common 6
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
21.7%
T 8
13.3%
t 8
13.3%
n 7
11.7%
a 6
10.0%
l 4
 
6.7%
s 4
 
6.7%
g 2
 
3.3%
d 1
 
1.7%
L 1
 
1.7%
Other values (6) 6
10.0%
Common
ValueCountFrequency (%)
5
83.3%
: 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 13
19.7%
T 8
12.1%
t 8
12.1%
n 7
10.6%
a 6
9.1%
5
 
7.6%
l 4
 
6.1%
s 4
 
6.1%
g 2
 
3.0%
d 1
 
1.5%
Other values (8) 8
12.1%

geapps_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:50.364573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.833333333
Min length2

Characters and Unicode

Total characters17
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row330
2nd row400
3rd row242
4th row938
5th row102
ValueCountFrequency (%)
91 1
16.7%
400 1
16.7%
938 1
16.7%
242 1
16.7%
102 1
16.7%
330 1
16.7%
2023-12-09T22:39:50.668764image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
23.5%
3 3
17.6%
2 3
17.6%
9 2
11.8%
1 2
11.8%
4 2
11.8%
8 1
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
23.5%
3 3
17.6%
2 3
17.6%
9 2
11.8%
1 2
11.8%
4 2
11.8%
8 1
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Common 17
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
23.5%
3 3
17.6%
2 3
17.6%
9 2
11.8%
1 2
11.8%
4 2
11.8%
8 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
23.5%
3 3
17.6%
2 3
17.6%
9 2
11.8%
1 2
11.8%
4 2
11.8%
8 1
 
5.9%

swdapps_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:50.813070image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.833333333
Min length1

Characters and Unicode

Total characters11
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row76
2nd row16
3rd row13
4th row32
5th row13
ValueCountFrequency (%)
13 2
33.3%
16 1
16.7%
32 1
16.7%
76 1
16.7%
5 1
16.7%
2023-12-09T22:39:51.074466image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
6 2
18.2%
2 1
 
9.1%
7 1
 
9.1%
5 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
6 2
18.2%
2 1
 
9.1%
7 1
 
9.1%
5 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
6 2
18.2%
2 1
 
9.1%
7 1
 
9.1%
5 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
27.3%
3 3
27.3%
6 2
18.2%
2 1
 
9.1%
7 1
 
9.1%
5 1
 
9.1%

geappsperseat_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:51.204624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row3
2nd row5
3rd row48
4th row16
5th row5
ValueCountFrequency (%)
5 2
33.3%
16 1
16.7%
4 1
16.7%
48 1
16.7%
3 1
16.7%
2023-12-09T22:39:52.196306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
1 1
12.5%
6 1
12.5%
8 1
12.5%
3 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
1 1
12.5%
6 1
12.5%
8 1
12.5%
3 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
1 1
12.5%
6 1
12.5%
8 1
12.5%
3 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
25.0%
4 2
25.0%
1 1
12.5%
6 1
12.5%
8 1
12.5%
3 1
12.5%

swdappsperseat_prog6
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:52.328251image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.166666667
Min length1

Characters and Unicode

Total characters7
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row2
2nd row1
3rd row7
4th row11
5th row3
ValueCountFrequency (%)
1 2
33.3%
7 1
16.7%
11 1
16.7%
2 1
16.7%
3 1
16.7%
2023-12-09T22:39:52.578148image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
57.1%
7 1
 
14.3%
2 1
 
14.3%
3 1
 
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
57.1%
7 1
 
14.3%
2 1
 
14.3%
3 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
57.1%
7 1
 
14.3%
2 1
 
14.3%
3 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
57.1%
7 1
 
14.3%
2 1
 
14.3%
3 1
 
14.3%

swdseats_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:52.751332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row33
2nd row21
3rd row2
4th row3
5th row5
ValueCountFrequency (%)
33 1
16.7%
5 1
16.7%
7 1
16.7%
21 1
16.7%
2 1
16.7%
3 1
16.7%
2023-12-09T22:39:53.039847image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3
37.5%
2 2
25.0%
5 1
 
12.5%
7 1
 
12.5%
1 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3
37.5%
2 2
25.0%
5 1
 
12.5%
7 1
 
12.5%
1 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3
37.5%
2 2
25.0%
5 1
 
12.5%
7 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3
37.5%
2 2
25.0%
5 1
 
12.5%
7 1
 
12.5%
1 1
 
12.5%

geseats_prog6
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:53.223325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters12
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row132
2nd row86
3rd row5
4th row57
5th row20
ValueCountFrequency (%)
57 1
16.7%
26 1
16.7%
20 1
16.7%
86 1
16.7%
132 1
16.7%
5 1
16.7%
2023-12-09T22:39:53.546445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
6 2
16.7%
7 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
1 1
 
8.3%
3 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
6 2
16.7%
7 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
1 1
 
8.3%
3 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
6 2
16.7%
7 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
1 1
 
8.3%
3 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
25.0%
5 2
16.7%
6 2
16.7%
7 1
 
8.3%
0 1
 
8.3%
8 1
 
8.3%
1 1
 
8.3%
3 1
 
8.3%

gefilled_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:53.654012image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%
2023-12-09T22:39:53.870808image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

swdfilled_prog6
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:53.976233image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row1
5th row1
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%
2023-12-09T22:39:54.202309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

eligibility_prog6
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:39:54.398210image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length42.16666667
Min length31

Characters and Unicode

Total characters253
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of District 21
4th rowOpen to New York City residents
5th rowOpen to students and residents of Brooklyn
ValueCountFrequency (%)
open 6
13.3%
to 6
13.3%
residents 6
13.3%
students 5
11.1%
and 5
11.1%
of 5
11.1%
district 4
8.9%
21 4
8.9%
brooklyn 1
 
2.2%
new 1
 
2.2%
Other values (2) 2
 
4.4%
2023-12-09T22:39:54.728697image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
75.9%
Space Separator 39
 
15.4%
Uppercase Letter 14
 
5.5%
Decimal Number 8
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 31
16.1%
s 26
13.5%
e 24
12.5%
n 23
12.0%
d 16
8.3%
i 15
7.8%
o 14
7.3%
r 12
 
6.2%
p 6
 
3.1%
f 5
 
2.6%
Other values (7) 20
10.4%
Uppercase Letter
ValueCountFrequency (%)
O 6
42.9%
D 4
28.6%
B 1
 
7.1%
N 1
 
7.1%
Y 1
 
7.1%
C 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
81.4%
Common 47
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 31
15.0%
s 26
12.6%
e 24
11.7%
n 23
11.2%
d 16
7.8%
i 15
7.3%
o 14
6.8%
r 12
 
5.8%
O 6
 
2.9%
p 6
 
2.9%
Other values (13) 33
16.0%
Common
ValueCountFrequency (%)
39
83.0%
2 4
 
8.5%
1 4
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

priority1_prog6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:54.921755image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:39:55.234290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog6
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:39:55.428222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:39:55.746325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

prefnote_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria1_prog6
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.5 KiB
2023-12-09T22:39:55.954326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length106
Mean length90.6
Min length18

Characters and Unicode

Total characters453
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
3rd rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
4th rowOn-Site Assessment
5th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 8
 
10.1%
students 4
 
5.1%
based 4
 
5.1%
tests 4
 
5.1%
talent 4
 
5.1%
21 4
 
5.1%
the 4
 
5.1%
score 4
 
5.1%
who 4
 
5.1%
their 4
 
5.1%
Other values (12) 35
44.3%
2023-12-09T22:39:56.324790image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
74
16.3%
e 55
12.1%
t 46
 
10.2%
s 40
 
8.8%
o 24
 
5.3%
r 21
 
4.6%
l 20
 
4.4%
n 19
 
4.2%
i 18
 
4.0%
a 18
 
4.0%
Other values (21) 118
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 348
76.8%
Space Separator 74
 
16.3%
Uppercase Letter 21
 
4.6%
Decimal Number 8
 
1.8%
Dash Punctuation 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 55
15.8%
t 46
13.2%
s 40
11.5%
o 24
 
6.9%
r 21
 
6.0%
l 20
 
5.7%
n 19
 
5.5%
i 18
 
5.2%
a 18
 
5.2%
h 16
 
4.6%
Other values (10) 71
20.4%
Uppercase Letter
ValueCountFrequency (%)
T 9
42.9%
S 5
23.8%
D 4
19.0%
O 1
 
4.8%
A 1
 
4.8%
M 1
 
4.8%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 369
81.5%
Common 84
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 55
14.9%
t 46
12.5%
s 40
10.8%
o 24
 
6.5%
r 21
 
5.7%
l 20
 
5.4%
n 19
 
5.1%
i 18
 
4.9%
a 18
 
4.9%
h 16
 
4.3%
Other values (16) 92
24.9%
Common
ValueCountFrequency (%)
74
88.1%
2 4
 
4.8%
1 4
 
4.8%
- 1
 
1.2%
/ 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 453
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
74
16.3%
e 55
12.1%
t 46
 
10.2%
s 40
 
8.8%
o 24
 
5.3%
r 21
 
4.6%
l 20
 
4.4%
n 19
 
4.2%
i 18
 
4.0%
a 18
 
4.0%
Other values (21) 118
26.0%

selectioncriteria2_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:56.533242image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.833333333
Min length5

Characters and Unicode

Total characters35
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096WI
2nd rowK098SC
3rd rowK228M
4th rowK239ME
5th rowK281SC
ValueCountFrequency (%)
k281sc 1
16.7%
k096wi 1
16.7%
k098sc 1
16.7%
k228m 1
16.7%
k303me 1
16.7%
k239me 1
16.7%
2023-12-09T22:39:56.845165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
8 3
8.6%
0 3
8.6%
9 3
8.6%
M 3
8.6%
3 3
8.6%
S 2
 
5.7%
C 2
 
5.7%
E 2
 
5.7%
Other values (4) 4
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
51.4%
Uppercase Letter 17
48.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 6
35.3%
M 3
17.6%
S 2
 
11.8%
C 2
 
11.8%
E 2
 
11.8%
W 1
 
5.9%
I 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
8 3
16.7%
0 3
16.7%
9 3
16.7%
3 3
16.7%
1 1
 
5.6%
6 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18
51.4%
Latin 17
48.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 6
35.3%
M 3
17.6%
S 2
 
11.8%
C 2
 
11.8%
E 2
 
11.8%
W 1
 
5.9%
I 1
 
5.9%
Common
ValueCountFrequency (%)
2 4
22.2%
8 3
16.7%
0 3
16.7%
9 3
16.7%
3 3
16.7%
1 1
 
5.6%
6 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
17.1%
2 4
11.4%
8 3
8.6%
0 3
8.6%
9 3
8.6%
M 3
8.6%
3 3
8.6%
S 2
 
5.7%
C 2
 
5.7%
E 2
 
5.7%
Other values (4) 4
11.4%

name_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.4 KiB
2023-12-09T22:39:57.107927image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length54.5
Mean length49.66666667
Min length29

Characters and Unicode

Total characters298
Distinct characters48
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSeth Low (I.S. 96) Magnet Program (Instrumental-Winds)
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Science)
3rd rowDavid A. Boody (I.S. 228): Chinese Dual Language Program
4th rowMark Twain (I.S. 239) (Media)
5th rowJoseph B. Cavallaro (I.S. 281) Magnet Program (Science)
ValueCountFrequency (%)
i.s 6
 
13.3%
program 5
 
11.1%
magnet 4
 
8.9%
science 2
 
4.4%
media 2
 
4.4%
281 1
 
2.2%
cavallaro 1
 
2.2%
b 1
 
2.2%
303 1
 
2.2%
joseph 1
 
2.2%
Other values (21) 21
46.7%
2023-12-09T22:39:57.474633image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
13.1%
a 23
 
7.7%
e 22
 
7.4%
r 16
 
5.4%
. 15
 
5.0%
n 13
 
4.4%
g 12
 
4.0%
) 11
 
3.7%
( 11
 
3.7%
S 10
 
3.4%
Other values (38) 126
42.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 158
53.0%
Uppercase Letter 46
 
15.4%
Space Separator 39
 
13.1%
Other Punctuation 16
 
5.4%
Decimal Number 16
 
5.4%
Close Punctuation 11
 
3.7%
Open Punctuation 11
 
3.7%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 23
14.6%
e 22
13.9%
r 16
10.1%
n 13
8.2%
g 12
 
7.6%
o 10
 
6.3%
i 9
 
5.7%
t 8
 
5.1%
m 7
 
4.4%
d 6
 
3.8%
Other values (11) 32
20.3%
Uppercase Letter
ValueCountFrequency (%)
S 10
21.7%
I 7
15.2%
M 7
15.2%
P 5
10.9%
B 3
 
6.5%
T 2
 
4.3%
D 2
 
4.3%
L 2
 
4.3%
C 2
 
4.3%
A 2
 
4.3%
Other values (4) 4
 
8.7%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
3 3
18.8%
9 3
18.8%
8 3
18.8%
6 1
 
6.2%
0 1
 
6.2%
1 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 15
93.8%
: 1
 
6.2%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 204
68.5%
Common 94
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 23
 
11.3%
e 22
 
10.8%
r 16
 
7.8%
n 13
 
6.4%
g 12
 
5.9%
S 10
 
4.9%
o 10
 
4.9%
i 9
 
4.4%
t 8
 
3.9%
I 7
 
3.4%
Other values (25) 74
36.3%
Common
ValueCountFrequency (%)
39
41.5%
. 15
 
16.0%
) 11
 
11.7%
( 11
 
11.7%
2 4
 
4.3%
3 3
 
3.2%
9 3
 
3.2%
8 3
 
3.2%
6 1
 
1.1%
- 1
 
1.1%
Other values (3) 3
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
 
13.1%
a 23
 
7.7%
e 22
 
7.4%
r 16
 
5.4%
. 15
 
5.0%
n 13
 
4.4%
g 12
 
4.0%
) 11
 
3.7%
( 11
 
3.7%
S 10
 
3.4%
Other values (38) 126
42.3%

admissionsmethod_prog7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:39:57.645454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length12.16666667
Min length11

Characters and Unicode

Total characters73
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st rowTalent Test
2nd rowTalent Test
3rd rowScreened: Language
4th rowTalent Test
5th rowTalent Test
ValueCountFrequency (%)
talent 5
41.7%
test 5
41.7%
screened 1
 
8.3%
language 1
 
8.3%
2023-12-09T22:39:57.933014image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 14
19.2%
T 10
13.7%
t 10
13.7%
a 7
9.6%
n 7
9.6%
6
8.2%
l 5
 
6.8%
s 5
 
6.8%
g 2
 
2.7%
S 1
 
1.4%
Other values (6) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 54
74.0%
Uppercase Letter 12
 
16.4%
Space Separator 6
 
8.2%
Other Punctuation 1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 14
25.9%
t 10
18.5%
a 7
13.0%
n 7
13.0%
l 5
 
9.3%
s 5
 
9.3%
g 2
 
3.7%
c 1
 
1.9%
r 1
 
1.9%
d 1
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
T 10
83.3%
S 1
 
8.3%
L 1
 
8.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 66
90.4%
Common 7
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 14
21.2%
T 10
15.2%
t 10
15.2%
a 7
10.6%
n 7
10.6%
l 5
 
7.6%
s 5
 
7.6%
g 2
 
3.0%
S 1
 
1.5%
c 1
 
1.5%
Other values (4) 4
 
6.1%
Common
ValueCountFrequency (%)
6
85.7%
: 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 14
19.2%
T 10
13.7%
t 10
13.7%
a 7
9.6%
n 7
9.6%
6
8.2%
l 5
 
6.8%
s 5
 
6.8%
g 2
 
2.7%
S 1
 
1.4%
Other values (6) 6
8.2%

geapps_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:58.120039image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.666666667
Min length2

Characters and Unicode

Total characters16
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row17
2nd row541
3rd row132
4th row264
5th row240
ValueCountFrequency (%)
17 1
16.7%
240 1
16.7%
24 1
16.7%
264 1
16.7%
541 1
16.7%
132 1
16.7%
2023-12-09T22:39:58.421716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
25.0%
4 4
25.0%
1 3
18.8%
7 1
 
6.2%
0 1
 
6.2%
6 1
 
6.2%
5 1
 
6.2%
3 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
25.0%
4 4
25.0%
1 3
18.8%
7 1
 
6.2%
0 1
 
6.2%
6 1
 
6.2%
5 1
 
6.2%
3 1
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
Common 16
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
25.0%
4 4
25.0%
1 3
18.8%
7 1
 
6.2%
0 1
 
6.2%
6 1
 
6.2%
5 1
 
6.2%
3 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
25.0%
4 4
25.0%
1 3
18.8%
7 1
 
6.2%
0 1
 
6.2%
6 1
 
6.2%
5 1
 
6.2%
3 1
 
6.2%

swdapps_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:58.589053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.666666667
Min length1

Characters and Unicode

Total characters10
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row3
2nd row30
3rd row10
4th row26
5th row25
ValueCountFrequency (%)
30 1
16.7%
25 1
16.7%
10 1
16.7%
26 1
16.7%
2 1
16.7%
3 1
16.7%
2023-12-09T22:39:58.866972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
30.0%
3 2
20.0%
0 2
20.0%
5 1
 
10.0%
1 1
 
10.0%
6 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
30.0%
3 2
20.0%
0 2
20.0%
5 1
 
10.0%
1 1
 
10.0%
6 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 3
30.0%
3 2
20.0%
0 2
20.0%
5 1
 
10.0%
1 1
 
10.0%
6 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
30.0%
3 2
20.0%
0 2
20.0%
5 1
 
10.0%
1 1
 
10.0%
6 1
 
10.0%

geseats_prog7
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:59.048278image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters12
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row24
2nd row57
3rd row45
4th row18
5th row20
ValueCountFrequency (%)
45 1
16.7%
22 1
16.7%
24 1
16.7%
57 1
16.7%
18 1
16.7%
20 1
16.7%
2023-12-09T22:39:59.345598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
33.3%
4 2
16.7%
5 2
16.7%
7 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
0 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
33.3%
4 2
16.7%
5 2
16.7%
7 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
0 1
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 12
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
33.3%
4 2
16.7%
5 2
16.7%
7 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
0 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
33.3%
4 2
16.7%
5 2
16.7%
7 1
 
8.3%
1 1
 
8.3%
8 1
 
8.3%
0 1
 
8.3%

swdseats_prog7
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:59.466860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)50.0%

Sample

1st row6
2nd row14
3rd row10
4th row6
5th row5
ValueCountFrequency (%)
6 3
50.0%
14 1
 
16.7%
10 1
 
16.7%
5 1
 
16.7%
2023-12-09T22:39:59.693901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 3
37.5%
1 2
25.0%
4 1
 
12.5%
0 1
 
12.5%
5 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 3
37.5%
1 2
25.0%
4 1
 
12.5%
0 1
 
12.5%
5 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 3
37.5%
1 2
25.0%
4 1
 
12.5%
0 1
 
12.5%
5 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 3
37.5%
1 2
25.0%
4 1
 
12.5%
0 1
 
12.5%
5 1
 
12.5%

geappsperseat_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:39:59.816538image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.333333333
Min length1

Characters and Unicode

Total characters8
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row1
2nd row9
3rd row3
4th row15
5th row12
ValueCountFrequency (%)
1 2
33.3%
12 1
16.7%
9 1
16.7%
15 1
16.7%
3 1
16.7%
2023-12-09T22:40:00.052849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
50.0%
2 1
 
12.5%
9 1
 
12.5%
5 1
 
12.5%
3 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
50.0%
2 1
 
12.5%
9 1
 
12.5%
5 1
 
12.5%
3 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
50.0%
2 1
 
12.5%
9 1
 
12.5%
5 1
 
12.5%
3 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
50.0%
2 1
 
12.5%
9 1
 
12.5%
5 1
 
12.5%
3 1
 
12.5%

swdappsperseat_prog7
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:00.178382image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)66.7%

Sample

1st row1
2nd row2
3rd row1
4th row4
5th row5
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
2 1
16.7%
5 1
16.7%
2023-12-09T22:40:00.428440image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
33.3%
4 1
16.7%
0 1
16.7%
2 1
16.7%
5 1
16.7%

gefilled_prog7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:00.538669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)16.7%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%
2023-12-09T22:40:00.758035image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 5
83.3%
0 1
 
16.7%

swdfilled_prog7
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:00.861363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%
2023-12-09T22:40:01.073467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

prefnote_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog7
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:40:01.260492image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length42.16666667
Min length31

Characters and Unicode

Total characters253
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of Brooklyn
4th rowOpen to New York City residents
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 6
13.3%
to 6
13.3%
residents 6
13.3%
students 5
11.1%
and 5
11.1%
of 5
11.1%
district 4
8.9%
21 4
8.9%
brooklyn 1
 
2.2%
new 1
 
2.2%
Other values (2) 2
 
4.4%
2023-12-09T22:40:01.572997image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192
75.9%
Space Separator 39
 
15.4%
Uppercase Letter 14
 
5.5%
Decimal Number 8
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 31
16.1%
s 26
13.5%
e 24
12.5%
n 23
12.0%
d 16
8.3%
i 15
7.8%
o 14
7.3%
r 12
 
6.2%
p 6
 
3.1%
f 5
 
2.6%
Other values (7) 20
10.4%
Uppercase Letter
ValueCountFrequency (%)
O 6
42.9%
D 4
28.6%
B 1
 
7.1%
N 1
 
7.1%
Y 1
 
7.1%
C 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 4
50.0%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 206
81.4%
Common 47
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 31
15.0%
s 26
12.6%
e 24
11.7%
n 23
11.2%
d 16
7.8%
i 15
7.3%
o 14
6.8%
r 12
 
5.8%
O 6
 
2.9%
p 6
 
2.9%
Other values (13) 33
16.0%
Common
ValueCountFrequency (%)
39
83.0%
2 4
 
8.5%
1 4
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
15.4%
t 31
12.3%
s 26
10.3%
e 24
9.5%
n 23
9.1%
d 16
 
6.3%
i 15
 
5.9%
o 14
 
5.5%
r 12
 
4.7%
O 6
 
2.4%
Other values (16) 47
18.6%

selectioncriteria1_prog7
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing468
Missing (%)98.7%
Memory size15.7 KiB
2023-12-09T22:40:01.785879image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length106
Mean length97.33333333
Min length43

Characters and Unicode

Total characters584
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)33.3%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
3rd row4th Grade New York State ELA and Math Exams
4th rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
5th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 10
 
9.5%
students 5
 
4.8%
based 5
 
4.8%
21 5
 
4.8%
who 5
 
4.8%
the 5
 
4.8%
score 5
 
4.8%
their 5
 
4.8%
selected 5
 
4.8%
tests 5
 
4.8%
Other values (19) 50
47.6%
2023-12-09T22:40:02.136712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
99
17.0%
e 68
11.6%
t 59
 
10.1%
s 46
 
7.9%
o 31
 
5.3%
r 28
 
4.8%
a 27
 
4.6%
l 25
 
4.3%
n 22
 
3.8%
h 22
 
3.8%
Other values (26) 157
26.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 442
75.7%
Space Separator 99
 
17.0%
Uppercase Letter 31
 
5.3%
Decimal Number 11
 
1.9%
Other Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 68
15.4%
t 59
13.3%
s 46
10.4%
o 31
 
7.0%
r 28
 
6.3%
a 27
 
6.1%
l 25
 
5.7%
n 22
 
5.0%
h 22
 
5.0%
i 21
 
4.8%
Other values (11) 93
21.0%
Uppercase Letter
ValueCountFrequency (%)
T 11
35.5%
S 6
19.4%
D 5
16.1%
M 2
 
6.5%
E 2
 
6.5%
Y 1
 
3.2%
A 1
 
3.2%
L 1
 
3.2%
N 1
 
3.2%
G 1
 
3.2%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
1 5
45.5%
4 1
 
9.1%
Space Separator
ValueCountFrequency (%)
99
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 473
81.0%
Common 111
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 68
14.4%
t 59
12.5%
s 46
 
9.7%
o 31
 
6.6%
r 28
 
5.9%
a 27
 
5.7%
l 25
 
5.3%
n 22
 
4.7%
h 22
 
4.7%
i 21
 
4.4%
Other values (21) 124
26.2%
Common
ValueCountFrequency (%)
99
89.2%
2 5
 
4.5%
1 5
 
4.5%
/ 1
 
0.9%
4 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 584
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
99
17.0%
e 68
11.6%
t 59
 
10.1%
s 46
 
7.9%
o 31
 
5.3%
r 28
 
4.8%
a 27
 
4.6%
l 25
 
4.3%
n 22
 
3.8%
h 22
 
3.8%
Other values (26) 157
26.9%

selectioncriteria2_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:02.339565image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAcademic and Personal Behavior Scores
ValueCountFrequency (%)
academic 1
20.0%
and 1
20.0%
personal 1
20.0%
behavior 1
20.0%
scores 1
20.0%
2023-12-09T22:40:02.660139image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29
78.4%
Space Separator 4
 
10.8%
Uppercase Letter 4
 
10.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
13.8%
e 4
13.8%
c 3
10.3%
r 3
10.3%
o 3
10.3%
d 2
6.9%
i 2
6.9%
n 2
6.9%
s 2
6.9%
v 1
 
3.4%
Other values (3) 3
10.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
B 1
25.0%
P 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
89.2%
Common 4
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
12.1%
e 4
12.1%
c 3
9.1%
r 3
9.1%
o 3
9.1%
d 2
 
6.1%
i 2
 
6.1%
n 2
 
6.1%
s 2
 
6.1%
A 1
 
3.0%
Other values (7) 7
21.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

selectioncriteria3_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:02.832006image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAttendance
ValueCountFrequency (%)
attendance 1
100.0%
2023-12-09T22:40:03.103088image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
90.0%
Uppercase Letter 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2
22.2%
e 2
22.2%
n 2
22.2%
d 1
11.1%
a 1
11.1%
c 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

selectioncriteria4_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:03.249531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLateness
ValueCountFrequency (%)
lateness 1
100.0%
2023-12-09T22:40:03.504664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
s 2
28.6%
a 1
14.3%
t 1
14.3%
n 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

selectioncriteria5_prog7
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:03.663865image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOn-Site Assessment
ValueCountFrequency (%)
on-site 1
50.0%
assessment 1
50.0%
2023-12-09T22:40:03.952549image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
72.2%
Uppercase Letter 3
 
16.7%
Dash Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 3
23.1%
n 2
15.4%
t 2
15.4%
i 1
 
7.7%
m 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
S 1
33.3%
A 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
25.0%
e 3
18.8%
n 2
12.5%
t 2
12.5%
O 1
 
6.2%
S 1
 
6.2%
i 1
 
6.2%
A 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

selectioncriteria6_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog8
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:04.136804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length5.5
Min length5

Characters and Unicode

Total characters33
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowK096Y
2nd rowK098ST
3rd rowK228N
4th rowK239SC
5th rowK281U
ValueCountFrequency (%)
k281u 1
16.7%
k239sc 1
16.7%
k096y 1
16.7%
k098st 1
16.7%
k228n 1
16.7%
k303sc 1
16.7%
2023-12-09T22:40:04.450235image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 6
18.2%
2 4
12.1%
8 3
9.1%
3 3
9.1%
9 3
9.1%
S 3
9.1%
0 3
9.1%
C 2
 
6.1%
1 1
 
3.0%
U 1
 
3.0%
Other values (4) 4
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18
54.5%
Uppercase Letter 15
45.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 6
40.0%
S 3
20.0%
C 2
 
13.3%
U 1
 
6.7%
Y 1
 
6.7%
T 1
 
6.7%
N 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
8 3
16.7%
3 3
16.7%
9 3
16.7%
0 3
16.7%
1 1
 
5.6%
6 1
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
Common 18
54.5%
Latin 15
45.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 6
40.0%
S 3
20.0%
C 2
 
13.3%
U 1
 
6.7%
Y 1
 
6.7%
T 1
 
6.7%
N 1
 
6.7%
Common
ValueCountFrequency (%)
2 4
22.2%
8 3
16.7%
3 3
16.7%
9 3
16.7%
0 3
16.7%
1 1
 
5.6%
6 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 6
18.2%
2 4
12.1%
8 3
9.1%
3 3
9.1%
9 3
9.1%
S 3
9.1%
0 3
9.1%
C 2
 
6.1%
1 1
 
3.0%
U 1
 
3.0%
Other values (4) 4
12.1%

name_prog8
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing468
Missing (%)98.7%
Memory size15.3 KiB
2023-12-09T22:40:04.680452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length65
Median length43.5
Mean length43.83333333
Min length25

Characters and Unicode

Total characters263
Distinct characters51
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSETH LOW ASD NEST PROGRAM
2nd rowThe Bay Academy (I.S. 98) Magnet Program (Instrumental - Strings)
3rd rowDavid A. Boody (I.S. 228): Russian Dual Language Program
4th rowMark Twain (I.S. 239) (Science)
5th rowJoseph B. Cavallaro (I.S. 281)
ValueCountFrequency (%)
i.s 5
 
11.9%
program 4
 
9.5%
magnet 2
 
4.8%
science 2
 
4.8%
the 1
 
2.4%
303 1
 
2.4%
mark 1
 
2.4%
twain 1
 
2.4%
239 1
 
2.4%
seth 1
 
2.4%
Other values (23) 23
54.8%
2023-12-09T22:40:05.052528image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
 
13.7%
a 18
 
6.8%
e 15
 
5.7%
r 13
 
4.9%
. 13
 
4.9%
S 12
 
4.6%
n 11
 
4.2%
g 9
 
3.4%
( 8
 
3.0%
) 8
 
3.0%
Other values (41) 120
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 125
47.5%
Uppercase Letter 57
21.7%
Space Separator 36
 
13.7%
Other Punctuation 14
 
5.3%
Decimal Number 14
 
5.3%
Open Punctuation 8
 
3.0%
Close Punctuation 8
 
3.0%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 18
14.4%
e 15
12.0%
r 13
10.4%
n 11
 
8.8%
g 9
 
7.2%
o 7
 
5.6%
i 7
 
5.6%
s 6
 
4.8%
t 6
 
4.8%
m 5
 
4.0%
Other values (11) 28
22.4%
Uppercase Letter
ValueCountFrequency (%)
S 12
21.1%
I 6
10.5%
M 4
 
7.0%
A 4
 
7.0%
P 4
 
7.0%
T 4
 
7.0%
E 3
 
5.3%
B 3
 
5.3%
D 3
 
5.3%
R 3
 
5.3%
Other values (8) 11
19.3%
Decimal Number
ValueCountFrequency (%)
2 4
28.6%
8 3
21.4%
3 3
21.4%
9 2
14.3%
1 1
 
7.1%
0 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 13
92.9%
: 1
 
7.1%
Space Separator
ValueCountFrequency (%)
36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 182
69.2%
Common 81
30.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 18
 
9.9%
e 15
 
8.2%
r 13
 
7.1%
S 12
 
6.6%
n 11
 
6.0%
g 9
 
4.9%
o 7
 
3.8%
i 7
 
3.8%
s 6
 
3.3%
t 6
 
3.3%
Other values (29) 78
42.9%
Common
ValueCountFrequency (%)
36
44.4%
. 13
 
16.0%
( 8
 
9.9%
) 8
 
9.9%
2 4
 
4.9%
8 3
 
3.7%
3 3
 
3.7%
9 2
 
2.5%
1 1
 
1.2%
: 1
 
1.2%
Other values (2) 2
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
 
13.7%
a 18
 
6.8%
e 15
 
5.7%
r 13
 
4.9%
. 13
 
4.9%
S 12
 
4.6%
n 11
 
4.2%
g 9
 
3.4%
( 8
 
3.0%
) 8
 
3.0%
Other values (41) 120
45.6%

admissionsmethod_prog8
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.2 KiB
2023-12-09T22:40:05.238844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length17
Mean length11.83333333
Min length4

Characters and Unicode

Total characters71
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)50.0%

Sample

1st rowASD/ACES Program
2nd rowTalent Test
3rd rowScreened: Language
4th rowTalent Test
5th rowOpen
ValueCountFrequency (%)
talent 3
27.3%
test 3
27.3%
open 1
 
9.1%
screened 1
 
9.1%
language 1
 
9.1%
asd/aces 1
 
9.1%
program 1
 
9.1%
2023-12-09T22:40:05.547397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11
15.5%
T 6
 
8.5%
n 6
 
8.5%
t 6
 
8.5%
a 6
 
8.5%
5
 
7.0%
l 3
 
4.2%
s 3
 
4.2%
g 3
 
4.2%
S 3
 
4.2%
Other values (16) 19
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47
66.2%
Uppercase Letter 17
 
23.9%
Space Separator 5
 
7.0%
Other Punctuation 2
 
2.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
23.4%
n 6
12.8%
t 6
12.8%
a 6
12.8%
l 3
 
6.4%
s 3
 
6.4%
g 3
 
6.4%
r 3
 
6.4%
o 1
 
2.1%
d 1
 
2.1%
Other values (4) 4
 
8.5%
Uppercase Letter
ValueCountFrequency (%)
T 6
35.3%
S 3
17.6%
A 2
 
11.8%
C 1
 
5.9%
P 1
 
5.9%
E 1
 
5.9%
D 1
 
5.9%
L 1
 
5.9%
O 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
: 1
50.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 64
90.1%
Common 7
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
17.2%
T 6
9.4%
n 6
9.4%
t 6
9.4%
a 6
9.4%
l 3
 
4.7%
s 3
 
4.7%
g 3
 
4.7%
S 3
 
4.7%
r 3
 
4.7%
Other values (13) 14
21.9%
Common
ValueCountFrequency (%)
5
71.4%
/ 1
 
14.3%
: 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 11
15.5%
T 6
 
8.5%
n 6
 
8.5%
t 6
 
8.5%
a 6
 
8.5%
5
 
7.0%
l 3
 
4.2%
s 3
 
4.2%
g 3
 
4.2%
S 3
 
4.2%
Other values (16) 19
26.8%

geapps_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:05.719730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8
Min length2

Characters and Unicode

Total characters14
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row76
2nd row194
3rd row1176
4th row450
5th row98
ValueCountFrequency (%)
98 1
20.0%
450 1
20.0%
194 1
20.0%
1176 1
20.0%
76 1
20.0%
2023-12-09T22:40:06.020715image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
21.4%
9 2
14.3%
4 2
14.3%
7 2
14.3%
6 2
14.3%
8 1
 
7.1%
5 1
 
7.1%
0 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
21.4%
9 2
14.3%
4 2
14.3%
7 2
14.3%
6 2
14.3%
8 1
 
7.1%
5 1
 
7.1%
0 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
21.4%
9 2
14.3%
4 2
14.3%
7 2
14.3%
6 2
14.3%
8 1
 
7.1%
5 1
 
7.1%
0 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
21.4%
9 2
14.3%
4 2
14.3%
7 2
14.3%
6 2
14.3%
8 1
 
7.1%
5 1
 
7.1%
0 1
 
7.1%

swdapps_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:06.195972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8
Min length1

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row4
2nd row11
3rd row54
4th row99
5th row13
ValueCountFrequency (%)
54 1
20.0%
13 1
20.0%
4 1
20.0%
99 1
20.0%
11 1
20.0%
2023-12-09T22:40:06.506375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
33.3%
4 2
22.2%
9 2
22.2%
5 1
 
11.1%
3 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
33.3%
4 2
22.2%
9 2
22.2%
5 1
 
11.1%
3 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
33.3%
4 2
22.2%
9 2
22.2%
5 1
 
11.1%
3 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
33.3%
4 2
22.2%
9 2
22.2%
5 1
 
11.1%
3 1
 
11.1%

geseats_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:06.689301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.2
Min length2

Characters and Unicode

Total characters11
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row29
2nd row53
3rd row27
4th row141
5th row22
ValueCountFrequency (%)
141 1
20.0%
29 1
20.0%
22 1
20.0%
53 1
20.0%
27 1
20.0%
2023-12-09T22:40:06.973105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
4 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
4 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
Common 11
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
4 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
36.4%
1 2
18.2%
4 1
 
9.1%
9 1
 
9.1%
5 1
 
9.1%
3 1
 
9.1%
7 1
 
9.1%

swdseats_prog8
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:07.129816image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.4
Min length1

Characters and Unicode

Total characters7
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row7
2nd row12
3rd row5
4th row35
5th row6
ValueCountFrequency (%)
12 1
20.0%
35 1
20.0%
7 1
20.0%
6 1
20.0%
5 1
20.0%
2023-12-09T22:40:07.419978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
28.6%
1 1
14.3%
2 1
14.3%
3 1
14.3%
7 1
14.3%
6 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
28.6%
1 1
14.3%
2 1
14.3%
3 1
14.3%
7 1
14.3%
6 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
28.6%
1 1
14.3%
2 1
14.3%
3 1
14.3%
7 1
14.3%
6 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
28.6%
1 1
14.3%
2 1
14.3%
3 1
14.3%
7 1
14.3%
6 1
14.3%

geappsperseat_prog8
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:07.552573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row3
2nd row4
3rd row44
4th row3
5th row4
ValueCountFrequency (%)
4 2
40.0%
3 2
40.0%
44 1
20.0%
2023-12-09T22:40:07.798861image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 4
66.7%
3 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 4
66.7%
3 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 4
66.7%
3 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 4
66.7%
3 2
33.3%

swdappsperseat_prog8
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:07.910980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters6
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row1
2nd row1
3rd row11
4th row3
5th row2
ValueCountFrequency (%)
1 2
40.0%
11 1
20.0%
2 1
20.0%
3 1
20.0%
2023-12-09T22:40:08.159599image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
66.7%
2 1
 
16.7%
3 1
 
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
66.7%
2 1
 
16.7%
3 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
66.7%
2 1
 
16.7%
3 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
66.7%
2 1
 
16.7%
3 1
 
16.7%

gefilled_prog8
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:08.271741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%
2023-12-09T22:40:08.505757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
66.7%
0 2
33.3%

swdfilled_prog8
Text

MISSING 

Distinct2
Distinct (%)33.3%
Missing468
Missing (%)98.7%
Memory size15.1 KiB
2023-12-09T22:40:08.615872image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters6
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%
2023-12-09T22:40:08.831032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
50.0%
0 3
50.0%

prefnote_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:09.010712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:40:09.326690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:09.511406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:40:09.806254image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog8
Text

MISSING 

Distinct4
Distinct (%)66.7%
Missing468
Missing (%)98.7%
Memory size15.5 KiB
2023-12-09T22:40:10.026710image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length200
Median length122.5
Mean length68
Min length31

Characters and Unicode

Total characters408
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)50.0%

Sample

1st rowOpen to students currently in an ASD (Autism Spectrum Disorder) Nest program. If you are not currently an ASD Nest student and are interested in the program, please contact asdprograms@schools.nyc.gov
2nd rowOpen to students and residents of District 21
3rd rowOpen to students and residents of Brooklyn
4th rowOpen to New York City residents
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 6
 
9.0%
to 6
 
9.0%
students 5
 
7.5%
and 5
 
7.5%
residents 5
 
7.5%
of 4
 
6.0%
district 3
 
4.5%
21 3
 
4.5%
asd 2
 
3.0%
are 2
 
3.0%
Other values (21) 26
38.8%
2023-12-09T22:40:10.380572image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61
15.0%
t 42
10.3%
e 37
 
9.1%
s 34
 
8.3%
n 33
 
8.1%
r 26
 
6.4%
o 23
 
5.6%
d 19
 
4.7%
i 17
 
4.2%
a 15
 
3.7%
Other values (28) 101
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 309
75.7%
Space Separator 61
 
15.0%
Uppercase Letter 25
 
6.1%
Decimal Number 6
 
1.5%
Other Punctuation 5
 
1.2%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 42
13.6%
e 37
12.0%
s 34
11.0%
n 33
10.7%
r 26
8.4%
o 23
7.4%
d 19
 
6.1%
i 17
 
5.5%
a 15
 
4.9%
u 11
 
3.6%
Other values (11) 52
16.8%
Uppercase Letter
ValueCountFrequency (%)
O 6
24.0%
D 6
24.0%
A 3
12.0%
S 3
12.0%
N 3
12.0%
I 1
 
4.0%
B 1
 
4.0%
Y 1
 
4.0%
C 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 1
 
20.0%
@ 1
 
20.0%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 334
81.9%
Common 74
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 42
12.6%
e 37
11.1%
s 34
10.2%
n 33
9.9%
r 26
 
7.8%
o 23
 
6.9%
d 19
 
5.7%
i 17
 
5.1%
a 15
 
4.5%
u 11
 
3.3%
Other values (20) 77
23.1%
Common
ValueCountFrequency (%)
61
82.4%
1 3
 
4.1%
2 3
 
4.1%
. 3
 
4.1%
) 1
 
1.4%
( 1
 
1.4%
, 1
 
1.4%
@ 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 408
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
61
15.0%
t 42
10.3%
e 37
 
9.1%
s 34
 
8.3%
n 33
 
8.1%
r 26
 
6.4%
o 23
 
5.6%
d 19
 
4.7%
i 17
 
4.2%
a 15
 
3.7%
Other values (28) 101
24.8%

selectioncriteria1_prog8
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.4 KiB
2023-12-09T22:40:10.623936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length111.5
Mean length93
Min length43

Characters and Unicode

Total characters372
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd row4th Grade New York State ELA and Math Exams
3rd rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
4th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 6
 
9.0%
students 3
 
4.5%
based 3
 
4.5%
21 3
 
4.5%
who 3
 
4.5%
the 3
 
4.5%
score 3
 
4.5%
their 3
 
4.5%
selected 3
 
4.5%
tests 3
 
4.5%
Other values (19) 34
50.7%
2023-12-09T22:40:10.971330image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
16.9%
e 42
11.3%
t 37
 
9.9%
s 28
 
7.5%
o 19
 
5.1%
a 19
 
5.1%
r 18
 
4.8%
l 15
 
4.0%
n 14
 
3.8%
h 14
 
3.8%
Other values (26) 103
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 278
74.7%
Space Separator 63
 
16.9%
Uppercase Letter 23
 
6.2%
Decimal Number 7
 
1.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
15.1%
t 37
13.3%
s 28
10.1%
o 19
 
6.8%
a 19
 
6.8%
r 18
 
6.5%
l 15
 
5.4%
n 14
 
5.0%
h 14
 
5.0%
i 13
 
4.7%
Other values (11) 59
21.2%
Uppercase Letter
ValueCountFrequency (%)
T 7
30.4%
S 4
17.4%
D 3
13.0%
M 2
 
8.7%
E 2
 
8.7%
Y 1
 
4.3%
A 1
 
4.3%
L 1
 
4.3%
N 1
 
4.3%
G 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
1 3
42.9%
4 1
 
14.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 301
80.9%
Common 71
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
14.0%
t 37
12.3%
s 28
 
9.3%
o 19
 
6.3%
a 19
 
6.3%
r 18
 
6.0%
l 15
 
5.0%
n 14
 
4.7%
h 14
 
4.7%
i 13
 
4.3%
Other values (21) 82
27.2%
Common
ValueCountFrequency (%)
63
88.7%
2 3
 
4.2%
1 3
 
4.2%
/ 1
 
1.4%
4 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
16.9%
e 42
11.3%
t 37
 
9.9%
s 28
 
7.5%
o 19
 
5.1%
a 19
 
5.1%
r 18
 
4.8%
l 15
 
4.0%
n 14
 
3.8%
h 14
 
3.8%
Other values (26) 103
27.7%

selectioncriteria2_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:11.150570image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAcademic and Personal Behavior Scores
ValueCountFrequency (%)
academic 1
20.0%
and 1
20.0%
personal 1
20.0%
behavior 1
20.0%
scores 1
20.0%
2023-12-09T22:40:11.443992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29
78.4%
Space Separator 4
 
10.8%
Uppercase Letter 4
 
10.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
13.8%
e 4
13.8%
c 3
10.3%
r 3
10.3%
o 3
10.3%
d 2
6.9%
i 2
6.9%
n 2
6.9%
s 2
6.9%
v 1
 
3.4%
Other values (3) 3
10.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
B 1
25.0%
P 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
89.2%
Common 4
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
12.1%
e 4
12.1%
c 3
9.1%
r 3
9.1%
o 3
9.1%
d 2
 
6.1%
i 2
 
6.1%
n 2
 
6.1%
s 2
 
6.1%
A 1
 
3.0%
Other values (7) 7
21.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

selectioncriteria3_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:11.600231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAttendance
ValueCountFrequency (%)
attendance 1
100.0%
2023-12-09T22:40:12.748719image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
90.0%
Uppercase Letter 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2
22.2%
e 2
22.2%
n 2
22.2%
d 1
11.1%
a 1
11.1%
c 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

selectioncriteria4_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:12.920084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters27
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowFinal 4th Grade Report Card
ValueCountFrequency (%)
final 1
20.0%
4th 1
20.0%
grade 1
20.0%
report 1
20.0%
card 1
20.0%
2023-12-09T22:40:13.205228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
66.7%
Space Separator 4
 
14.8%
Uppercase Letter 4
 
14.8%
Decimal Number 1
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
a 3
16.7%
t 2
11.1%
e 2
11.1%
d 2
11.1%
o 1
 
5.6%
p 1
 
5.6%
h 1
 
5.6%
i 1
 
5.6%
l 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
F 1
25.0%
R 1
25.0%
G 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22
81.5%
Common 5
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 3
13.6%
a 3
13.6%
t 2
 
9.1%
e 2
 
9.1%
d 2
 
9.1%
F 1
 
4.5%
o 1
 
4.5%
p 1
 
4.5%
R 1
 
4.5%
h 1
 
4.5%
Other values (5) 5
22.7%
Common
ValueCountFrequency (%)
4
80.0%
4 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

selectioncriteria5_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:13.355520image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLateness
ValueCountFrequency (%)
lateness 1
100.0%
2023-12-09T22:40:13.609803image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
s 2
28.6%
a 1
14.3%
t 1
14.3%
n 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

selectioncriteria6_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:13.769643image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOn-Site Assessment
ValueCountFrequency (%)
on-site 1
50.0%
assessment 1
50.0%
2023-12-09T22:40:14.041325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
72.2%
Uppercase Letter 3
 
16.7%
Dash Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 3
23.1%
n 2
15.4%
t 2
15.4%
i 1
 
7.7%
m 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
S 1
33.3%
A 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
25.0%
e 3
18.8%
n 2
12.5%
t 2
12.5%
O 1
 
6.2%
S 1
 
6.2%
i 1
 
6.2%
A 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

selectioncriteria7_prog8
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:14.227932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowReading, Writing and Oral Comprehension
ValueCountFrequency (%)
reading 1
20.0%
writing 1
20.0%
and 1
20.0%
oral 1
20.0%
comprehension 1
20.0%
2023-12-09T22:40:14.535868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 5
12.8%
i 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
a 3
 
7.7%
e 3
 
7.7%
d 2
 
5.1%
g 2
 
5.1%
o 2
 
5.1%
C 1
 
2.6%
Other values (10) 10
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30
76.9%
Space Separator 4
 
10.3%
Uppercase Letter 4
 
10.3%
Other Punctuation 1
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 5
16.7%
i 4
13.3%
r 3
10.0%
a 3
10.0%
e 3
10.0%
d 2
 
6.7%
g 2
 
6.7%
o 2
 
6.7%
h 1
 
3.3%
p 1
 
3.3%
Other values (4) 4
13.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
25.0%
R 1
25.0%
O 1
25.0%
W 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
87.2%
Common 5
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 5
14.7%
i 4
11.8%
r 3
 
8.8%
a 3
 
8.8%
e 3
 
8.8%
d 2
 
5.9%
g 2
 
5.9%
o 2
 
5.9%
C 1
 
2.9%
h 1
 
2.9%
Other values (8) 8
23.5%
Common
ValueCountFrequency (%)
4
80.0%
, 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 5
12.8%
i 4
 
10.3%
4
 
10.3%
r 3
 
7.7%
a 3
 
7.7%
e 3
 
7.7%
d 2
 
5.1%
g 2
 
5.1%
o 2
 
5.1%
C 1
 
2.6%
Other values (10) 10
25.6%

selectioncriteria8_prog8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:14.718306image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6
Min length5

Characters and Unicode

Total characters28
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowK098VO
2nd rowK228P
3rd rowK239ST
4th rowK281VO
5th rowK303U
ValueCountFrequency (%)
k281vo 1
20.0%
k228p 1
20.0%
k098vo 1
20.0%
k303u 1
20.0%
k239st 1
20.0%
2023-12-09T22:40:15.014757image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 5
17.9%
2 4
14.3%
8 3
10.7%
3 3
10.7%
V 2
 
7.1%
O 2
 
7.1%
0 2
 
7.1%
9 2
 
7.1%
1 1
 
3.6%
P 1
 
3.6%
Other values (3) 3
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15
53.6%
Uppercase Letter 13
46.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 5
38.5%
V 2
 
15.4%
O 2
 
15.4%
P 1
 
7.7%
U 1
 
7.7%
S 1
 
7.7%
T 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
2 4
26.7%
8 3
20.0%
3 3
20.0%
0 2
13.3%
9 2
13.3%
1 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 15
53.6%
Latin 13
46.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 5
38.5%
V 2
 
15.4%
O 2
 
15.4%
P 1
 
7.7%
U 1
 
7.7%
S 1
 
7.7%
T 1
 
7.7%
Common
ValueCountFrequency (%)
2 4
26.7%
8 3
20.0%
3 3
20.0%
0 2
13.3%
9 2
13.3%
1 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 5
17.9%
2 4
14.3%
8 3
10.7%
3 3
10.7%
V 2
 
7.1%
O 2
 
7.1%
0 2
 
7.1%
9 2
 
7.1%
1 1
 
3.6%
P 1
 
3.6%
Other values (3) 3
10.7%

name_prog9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.3 KiB
2023-12-09T22:40:15.235873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length62
Median length56
Mean length54.6
Min length42

Characters and Unicode

Total characters273
Distinct characters48
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st rowThe Bay Academy (I.S. 98) Magnet Program (Vocal Music)
2nd rowDavid A. Boody (I.S. 228): Spanish Dual Language Program
3rd rowMark Twain (I.S. 239) (String Instruments)
4th rowJoseph B. Cavallaro (I.S. 281) Magnet Program (Vocal Music)
5th rowHerbert S. Eisenberg (I.S. 303) Academy for Career Exploration
ValueCountFrequency (%)
i.s 5
 
11.9%
program 3
 
7.1%
academy 2
 
4.8%
magnet 2
 
4.8%
music 2
 
4.8%
vocal 2
 
4.8%
303 1
 
2.4%
for 1
 
2.4%
career 1
 
2.4%
exploration 1
 
2.4%
Other values (22) 22
52.4%
2023-12-09T22:40:15.615464image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
 
13.6%
a 22
 
8.1%
r 17
 
6.2%
e 14
 
5.1%
. 13
 
4.8%
o 12
 
4.4%
n 10
 
3.7%
g 9
 
3.3%
i 8
 
2.9%
S 8
 
2.9%
Other values (38) 123
45.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 151
55.3%
Uppercase Letter 41
 
15.0%
Space Separator 37
 
13.6%
Other Punctuation 14
 
5.1%
Decimal Number 14
 
5.1%
Close Punctuation 8
 
2.9%
Open Punctuation 8
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 22
14.6%
r 17
11.3%
e 14
 
9.3%
o 12
 
7.9%
n 10
 
6.6%
g 9
 
6.0%
i 8
 
5.3%
s 7
 
4.6%
t 7
 
4.6%
l 6
 
4.0%
Other values (13) 39
25.8%
Uppercase Letter
ValueCountFrequency (%)
S 8
19.5%
I 6
14.6%
M 5
12.2%
B 3
 
7.3%
A 3
 
7.3%
P 3
 
7.3%
D 2
 
4.9%
E 2
 
4.9%
V 2
 
4.9%
T 2
 
4.9%
Other values (4) 5
12.2%
Decimal Number
ValueCountFrequency (%)
2 4
28.6%
3 3
21.4%
8 3
21.4%
9 2
14.3%
1 1
 
7.1%
0 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
. 13
92.9%
: 1
 
7.1%
Space Separator
ValueCountFrequency (%)
37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 192
70.3%
Common 81
29.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 22
 
11.5%
r 17
 
8.9%
e 14
 
7.3%
o 12
 
6.2%
n 10
 
5.2%
g 9
 
4.7%
i 8
 
4.2%
S 8
 
4.2%
s 7
 
3.6%
t 7
 
3.6%
Other values (27) 78
40.6%
Common
ValueCountFrequency (%)
37
45.7%
. 13
 
16.0%
) 8
 
9.9%
( 8
 
9.9%
2 4
 
4.9%
3 3
 
3.7%
8 3
 
3.7%
9 2
 
2.5%
1 1
 
1.2%
0 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
 
13.6%
a 22
 
8.1%
r 17
 
6.2%
e 14
 
5.1%
. 13
 
4.8%
o 12
 
4.4%
n 10
 
3.7%
g 9
 
3.3%
i 8
 
2.9%
S 8
 
2.9%
Other values (38) 123
45.1%

admissionsmethod_prog9
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:15.786181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length11
Min length4

Characters and Unicode

Total characters55
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowTalent Test
2nd rowScreened: Language
3rd rowTalent Test
4th rowTalent Test
5th rowOpen
ValueCountFrequency (%)
talent 3
33.3%
test 3
33.3%
open 1
 
11.1%
screened 1
 
11.1%
language 1
 
11.1%
2023-12-09T22:40:16.079303image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11
20.0%
T 6
10.9%
n 6
10.9%
t 6
10.9%
a 5
9.1%
4
 
7.3%
l 3
 
5.5%
s 3
 
5.5%
g 2
 
3.6%
d 1
 
1.8%
Other values (8) 8
14.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41
74.5%
Uppercase Letter 9
 
16.4%
Space Separator 4
 
7.3%
Other Punctuation 1
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 11
26.8%
n 6
14.6%
t 6
14.6%
a 5
12.2%
l 3
 
7.3%
s 3
 
7.3%
g 2
 
4.9%
d 1
 
2.4%
p 1
 
2.4%
r 1
 
2.4%
Other values (2) 2
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
T 6
66.7%
L 1
 
11.1%
S 1
 
11.1%
O 1
 
11.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 50
90.9%
Common 5
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 11
22.0%
T 6
12.0%
n 6
12.0%
t 6
12.0%
a 5
10.0%
l 3
 
6.0%
s 3
 
6.0%
g 2
 
4.0%
d 1
 
2.0%
L 1
 
2.0%
Other values (6) 6
12.0%
Common
ValueCountFrequency (%)
4
80.0%
: 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 11
20.0%
T 6
10.9%
n 6
10.9%
t 6
10.9%
a 5
9.1%
4
 
7.3%
l 3
 
5.5%
s 3
 
5.5%
g 2
 
3.6%
d 1
 
1.8%
Other values (8) 8
14.5%

geapps_prog9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:16.248636image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8
Min length2

Characters and Unicode

Total characters14
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row116
2nd row127
3rd row253
4th row44
5th row147
ValueCountFrequency (%)
127 1
20.0%
116 1
20.0%
147 1
20.0%
44 1
20.0%
253 1
20.0%
2023-12-09T22:40:16.539468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4
28.6%
4 3
21.4%
2 2
14.3%
7 2
14.3%
6 1
 
7.1%
5 1
 
7.1%
3 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
28.6%
4 3
21.4%
2 2
14.3%
7 2
14.3%
6 1
 
7.1%
5 1
 
7.1%
3 1
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
28.6%
4 3
21.4%
2 2
14.3%
7 2
14.3%
6 1
 
7.1%
5 1
 
7.1%
3 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
28.6%
4 3
21.4%
2 2
14.3%
7 2
14.3%
6 1
 
7.1%
5 1
 
7.1%
3 1
 
7.1%

swdapps_prog9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:16.704456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.8
Min length1

Characters and Unicode

Total characters9
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row16
2nd row30
3rd row13
4th row9
5th row31
ValueCountFrequency (%)
30 1
20.0%
13 1
20.0%
16 1
20.0%
31 1
20.0%
9 1
20.0%
2023-12-09T22:40:16.976160image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3
33.3%
1 3
33.3%
0 1
 
11.1%
6 1
 
11.1%
9 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3
33.3%
1 3
33.3%
0 1
 
11.1%
6 1
 
11.1%
9 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 3
33.3%
1 3
33.3%
0 1
 
11.1%
6 1
 
11.1%
9 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 3
33.3%
1 3
33.3%
0 1
 
11.1%
6 1
 
11.1%
9 1
 
11.1%

geseats_prog9
Text

MISSING 

Distinct4
Distinct (%)80.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:17.118173image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters10
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)60.0%

Sample

1st row26
2nd row24
3rd row25
4th row24
5th row53
ValueCountFrequency (%)
24 2
40.0%
25 1
20.0%
53 1
20.0%
26 1
20.0%
2023-12-09T22:40:17.367561image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
40.0%
4 2
20.0%
5 2
20.0%
3 1
 
10.0%
6 1
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
40.0%
4 2
20.0%
5 2
20.0%
3 1
 
10.0%
6 1
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
40.0%
4 2
20.0%
5 2
20.0%
3 1
 
10.0%
6 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
40.0%
4 2
20.0%
5 2
20.0%
3 1
 
10.0%
6 1
 
10.0%

swdseats_prog9
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:17.496374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row7
2nd row6
3rd row7
4th row6
5th row14
ValueCountFrequency (%)
7 2
40.0%
6 2
40.0%
14 1
20.0%
2023-12-09T22:40:17.737949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 2
33.3%
6 2
33.3%
1 1
16.7%
4 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 2
33.3%
6 2
33.3%
1 1
16.7%
4 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 2
33.3%
6 2
33.3%
1 1
16.7%
4 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 2
33.3%
6 2
33.3%
1 1
16.7%
4 1
16.7%

geappsperseat_prog9
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:17.901841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.2
Min length1

Characters and Unicode

Total characters6
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)100.0%

Sample

1st row4
2nd row5
3rd row10
4th row2
5th row3
ValueCountFrequency (%)
3 1
20.0%
10 1
20.0%
4 1
20.0%
2 1
20.0%
5 1
20.0%
2023-12-09T22:40:18.185497image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
0 1
16.7%
4 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
0 1
16.7%
4 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
0 1
16.7%
4 1
16.7%
2 1
16.7%
5 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1
16.7%
1 1
16.7%
0 1
16.7%
4 1
16.7%
2 1
16.7%
5 1
16.7%

swdappsperseat_prog9
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:18.300282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row2
2nd row5
3rd row2
4th row2
5th row2
ValueCountFrequency (%)
2 4
80.0%
5 1
 
20.0%
2023-12-09T22:40:18.535503image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
80.0%
5 1
 
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
80.0%
5 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
80.0%
5 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
80.0%
5 1
 
20.0%

gefilled_prog9
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:18.647130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row0
ValueCountFrequency (%)
1 3
60.0%
0 2
40.0%
2023-12-09T22:40:18.866397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3
60.0%
0 2
40.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
60.0%
0 2
40.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
60.0%
0 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
60.0%
0 2
40.0%

swdfilled_prog9
Text

MISSING 

Distinct2
Distinct (%)40.0%
Missing469
Missing (%)98.9%
Memory size15.1 KiB
2023-12-09T22:40:18.976073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters5
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 4
80.0%
1 1
 
20.0%
2023-12-09T22:40:19.201536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
80.0%
1 1
 
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
80.0%
1 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
80.0%
1 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
80.0%
1 1
 
20.0%

prefnote_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:19.384219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length47
Median length47
Mean length47
Min length47

Characters and Unicode

Total characters47
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowPriority to residents of the middle school zone
ValueCountFrequency (%)
priority 1
12.5%
to 1
12.5%
residents 1
12.5%
of 1
12.5%
the 1
12.5%
middle 1
12.5%
school 1
12.5%
zone 1
12.5%
2023-12-09T22:40:19.680231image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 39
83.0%
Space Separator 7
 
14.9%
Uppercase Letter 1
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
15.4%
e 5
12.8%
i 4
10.3%
t 4
10.3%
s 3
7.7%
r 3
7.7%
d 3
7.7%
n 2
 
5.1%
l 2
 
5.1%
h 2
 
5.1%
Other values (5) 5
12.8%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40
85.1%
Common 7
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
15.0%
e 5
12.5%
i 4
10.0%
t 4
10.0%
s 3
7.5%
r 3
7.5%
d 3
7.5%
n 2
 
5.0%
l 2
 
5.0%
h 2
 
5.0%
Other values (6) 6
15.0%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
14.9%
o 6
12.8%
e 5
10.6%
i 4
8.5%
t 4
8.5%
s 3
 
6.4%
r 3
 
6.4%
d 3
 
6.4%
n 2
 
4.3%
l 2
 
4.3%
Other values (7) 8
17.0%

priority2_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:19.864682image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowThen to District 21 students and residents
ValueCountFrequency (%)
then 1
14.3%
to 1
14.3%
district 1
14.3%
21 1
14.3%
students 1
14.3%
and 1
14.3%
residents 1
14.3%
2023-12-09T22:40:20.177258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
76.2%
Space Separator 6
 
14.3%
Decimal Number 2
 
4.8%
Uppercase Letter 2
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
18.8%
s 5
15.6%
e 4
12.5%
n 4
12.5%
i 3
9.4%
d 3
9.4%
r 2
 
6.2%
u 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (2) 2
 
6.2%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
81.0%
Common 8
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
i 3
8.8%
d 3
8.8%
r 2
 
5.9%
u 1
 
2.9%
T 1
 
2.9%
c 1
 
2.9%
Other values (4) 4
11.8%
Common
ValueCountFrequency (%)
6
75.0%
2 1
 
12.5%
1 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
14.3%
t 6
14.3%
s 5
11.9%
e 4
9.5%
n 4
9.5%
i 3
7.1%
d 3
7.1%
r 2
 
4.8%
2 1
 
2.4%
u 1
 
2.4%
Other values (7) 7
16.7%

priority3_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog9
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing469
Missing (%)98.9%
Memory size15.3 KiB
2023-12-09T22:40:20.382941image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length41.6
Min length31

Characters and Unicode

Total characters208
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)40.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of Brooklyn
3rd rowOpen to New York City residents
4th rowOpen to students and residents of District 21
5th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 5
13.5%
to 5
13.5%
residents 5
13.5%
students 4
10.8%
and 4
10.8%
of 4
10.8%
district 3
8.1%
21 3
8.1%
brooklyn 1
 
2.7%
new 1
 
2.7%
Other values (2) 2
 
5.4%
2023-12-09T22:40:20.700954image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
15.4%
t 25
12.0%
s 21
10.1%
e 20
9.6%
n 19
9.1%
d 13
 
6.2%
o 12
 
5.8%
i 12
 
5.8%
r 10
 
4.8%
O 5
 
2.4%
Other values (16) 39
18.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 158
76.0%
Space Separator 32
 
15.4%
Uppercase Letter 12
 
5.8%
Decimal Number 6
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 25
15.8%
s 21
13.3%
e 20
12.7%
n 19
12.0%
d 13
8.2%
o 12
7.6%
i 12
7.6%
r 10
 
6.3%
p 5
 
3.2%
f 4
 
2.5%
Other values (7) 17
10.8%
Uppercase Letter
ValueCountFrequency (%)
O 5
41.7%
D 3
25.0%
B 1
 
8.3%
N 1
 
8.3%
Y 1
 
8.3%
C 1
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 170
81.7%
Common 38
 
18.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 25
14.7%
s 21
12.4%
e 20
11.8%
n 19
11.2%
d 13
7.6%
o 12
7.1%
i 12
7.1%
r 10
 
5.9%
O 5
 
2.9%
p 5
 
2.9%
Other values (13) 28
16.5%
Common
ValueCountFrequency (%)
32
84.2%
2 3
 
7.9%
1 3
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 208
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
15.4%
t 25
12.0%
s 21
10.1%
e 20
9.6%
n 19
9.1%
d 13
 
6.2%
o 12
 
5.8%
i 12
 
5.8%
r 10
 
4.8%
O 5
 
2.4%
Other values (16) 39
18.8%

selectioncriteria1_prog9
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.4 KiB
2023-12-09T22:40:20.916008image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length111.5
Mean length93
Min length43

Characters and Unicode

Total characters372
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd row4th Grade New York State ELA and Math Exams
3rd rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
4th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 6
 
9.0%
students 3
 
4.5%
based 3
 
4.5%
21 3
 
4.5%
who 3
 
4.5%
the 3
 
4.5%
score 3
 
4.5%
their 3
 
4.5%
selected 3
 
4.5%
tests 3
 
4.5%
Other values (19) 34
50.7%
2023-12-09T22:40:21.277177image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
16.9%
e 42
11.3%
t 37
 
9.9%
s 28
 
7.5%
o 19
 
5.1%
a 19
 
5.1%
r 18
 
4.8%
l 15
 
4.0%
n 14
 
3.8%
h 14
 
3.8%
Other values (26) 103
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 278
74.7%
Space Separator 63
 
16.9%
Uppercase Letter 23
 
6.2%
Decimal Number 7
 
1.9%
Other Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
15.1%
t 37
13.3%
s 28
10.1%
o 19
 
6.8%
a 19
 
6.8%
r 18
 
6.5%
l 15
 
5.4%
n 14
 
5.0%
h 14
 
5.0%
i 13
 
4.7%
Other values (11) 59
21.2%
Uppercase Letter
ValueCountFrequency (%)
T 7
30.4%
S 4
17.4%
D 3
13.0%
M 2
 
8.7%
E 2
 
8.7%
Y 1
 
4.3%
A 1
 
4.3%
L 1
 
4.3%
N 1
 
4.3%
G 1
 
4.3%
Decimal Number
ValueCountFrequency (%)
2 3
42.9%
1 3
42.9%
4 1
 
14.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 301
80.9%
Common 71
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
14.0%
t 37
12.3%
s 28
 
9.3%
o 19
 
6.3%
a 19
 
6.3%
r 18
 
6.0%
l 15
 
5.0%
n 14
 
4.7%
h 14
 
4.7%
i 13
 
4.3%
Other values (21) 82
27.2%
Common
ValueCountFrequency (%)
63
88.7%
2 3
 
4.2%
1 3
 
4.2%
/ 1
 
1.4%
4 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
16.9%
e 42
11.3%
t 37
 
9.9%
s 28
 
7.5%
o 19
 
5.1%
a 19
 
5.1%
r 18
 
4.8%
l 15
 
4.0%
n 14
 
3.8%
h 14
 
3.8%
Other values (26) 103
27.7%

selectioncriteria2_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:21.457005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAcademic and Personal Behavior Scores
ValueCountFrequency (%)
academic 1
20.0%
and 1
20.0%
personal 1
20.0%
behavior 1
20.0%
scores 1
20.0%
2023-12-09T22:40:21.745642image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29
78.4%
Space Separator 4
 
10.8%
Uppercase Letter 4
 
10.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4
13.8%
e 4
13.8%
c 3
10.3%
r 3
10.3%
o 3
10.3%
d 2
6.9%
i 2
6.9%
n 2
6.9%
s 2
6.9%
v 1
 
3.4%
Other values (3) 3
10.3%
Uppercase Letter
ValueCountFrequency (%)
A 1
25.0%
B 1
25.0%
P 1
25.0%
S 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 33
89.2%
Common 4
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4
12.1%
e 4
12.1%
c 3
9.1%
r 3
9.1%
o 3
9.1%
d 2
 
6.1%
i 2
 
6.1%
n 2
 
6.1%
s 2
 
6.1%
A 1
 
3.0%
Other values (7) 7
21.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4
10.8%
e 4
10.8%
4
10.8%
c 3
 
8.1%
r 3
 
8.1%
o 3
 
8.1%
d 2
 
5.4%
i 2
 
5.4%
n 2
 
5.4%
s 2
 
5.4%
Other values (8) 8
21.6%

selectioncriteria3_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:21.903043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters10
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowAttendance
ValueCountFrequency (%)
attendance 1
100.0%
2023-12-09T22:40:22.178239image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
90.0%
Uppercase Letter 1
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2
22.2%
e 2
22.2%
n 2
22.2%
d 1
11.1%
a 1
11.1%
c 1
11.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 2
20.0%
e 2
20.0%
n 2
20.0%
A 1
10.0%
d 1
10.0%
a 1
10.0%
c 1
10.0%

selectioncriteria4_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:22.362530image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length27
Median length27
Mean length27
Min length27

Characters and Unicode

Total characters27
Distinct characters17
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowFinal 4th Grade Report Card
ValueCountFrequency (%)
final 1
20.0%
4th 1
20.0%
grade 1
20.0%
report 1
20.0%
card 1
20.0%
2023-12-09T22:40:22.662807image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
66.7%
Space Separator 4
 
14.8%
Uppercase Letter 4
 
14.8%
Decimal Number 1
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
a 3
16.7%
t 2
11.1%
e 2
11.1%
d 2
11.1%
o 1
 
5.6%
p 1
 
5.6%
h 1
 
5.6%
i 1
 
5.6%
l 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
F 1
25.0%
R 1
25.0%
G 1
25.0%
C 1
25.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22
81.5%
Common 5
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 3
13.6%
a 3
13.6%
t 2
 
9.1%
e 2
 
9.1%
d 2
 
9.1%
F 1
 
4.5%
o 1
 
4.5%
p 1
 
4.5%
R 1
 
4.5%
h 1
 
4.5%
Other values (5) 5
22.7%
Common
ValueCountFrequency (%)
4
80.0%
4 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
14.8%
r 3
11.1%
a 3
11.1%
t 2
 
7.4%
e 2
 
7.4%
d 2
 
7.4%
F 1
 
3.7%
o 1
 
3.7%
p 1
 
3.7%
R 1
 
3.7%
Other values (7) 7
25.9%

selectioncriteria5_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:22.818745image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowLateness
ValueCountFrequency (%)
lateness 1
100.0%
2023-12-09T22:40:23.075058image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7
87.5%
Uppercase Letter 1
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
28.6%
s 2
28.6%
a 1
14.3%
t 1
14.3%
n 1
14.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2
25.0%
s 2
25.0%
L 1
12.5%
a 1
12.5%
t 1
12.5%
n 1
12.5%

selectioncriteria6_prog9
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:23.238272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters11
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOn-Site Assessment
ValueCountFrequency (%)
on-site 1
50.0%
assessment 1
50.0%
2023-12-09T22:40:23.511558image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
72.2%
Uppercase Letter 3
 
16.7%
Dash Punctuation 1
 
5.6%
Space Separator 1
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 4
30.8%
e 3
23.1%
n 2
15.4%
t 2
15.4%
i 1
 
7.7%
m 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
O 1
33.3%
S 1
33.3%
A 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
88.9%
Common 2
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 4
25.0%
e 3
18.8%
n 2
12.5%
t 2
12.5%
O 1
 
6.2%
S 1
 
6.2%
i 1
 
6.2%
A 1
 
6.2%
m 1
 
6.2%
Common
ValueCountFrequency (%)
- 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 4
22.2%
e 3
16.7%
n 2
11.1%
t 2
11.1%
O 1
 
5.6%
- 1
 
5.6%
S 1
 
5.6%
i 1
 
5.6%
1
 
5.6%
A 1
 
5.6%

selectioncriteria7_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog10
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.1 KiB
2023-12-09T22:40:23.687944image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.75
Min length5

Characters and Unicode

Total characters23
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowK098WI
2nd rowK228Q
3rd rowK239VO
4th rowK303VO
ValueCountFrequency (%)
k098wi 1
25.0%
k303vo 1
25.0%
k228q 1
25.0%
k239vo 1
25.0%
2023-12-09T22:40:23.987582image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 4
17.4%
3 3
13.0%
2 3
13.0%
0 2
8.7%
9 2
8.7%
8 2
8.7%
V 2
8.7%
O 2
8.7%
W 1
 
4.3%
I 1
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
52.2%
Uppercase Letter 11
47.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 4
36.4%
V 2
18.2%
O 2
18.2%
W 1
 
9.1%
I 1
 
9.1%
Q 1
 
9.1%
Decimal Number
ValueCountFrequency (%)
3 3
25.0%
2 3
25.0%
0 2
16.7%
9 2
16.7%
8 2
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 12
52.2%
Latin 11
47.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 4
36.4%
V 2
18.2%
O 2
18.2%
W 1
 
9.1%
I 1
 
9.1%
Q 1
 
9.1%
Common
ValueCountFrequency (%)
3 3
25.0%
2 3
25.0%
0 2
16.7%
9 2
16.7%
8 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 4
17.4%
3 3
13.0%
2 3
13.0%
0 2
8.7%
9 2
8.7%
8 2
8.7%
V 2
8.7%
O 2
8.7%
W 1
 
4.3%
I 1
 
4.3%

name_prog10
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.2 KiB
2023-12-09T22:40:24.203839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length57.5
Mean length51.75
Min length29

Characters and Unicode

Total characters207
Distinct characters44
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st rowThe Bay Academy (I.S. 98) Magnet Program (Instrumental - Winds)
2nd rowDavid A. Boody (I.S. 228): Hebrew Dual Language Program
3rd rowMark Twain (I.S. 239) (Vocal)
4th rowHerbert S. Eisenberg (I.S. 303) Magnet Program (Vocal Music)
ValueCountFrequency (%)
i.s 4
 
12.1%
program 3
 
9.1%
magnet 2
 
6.1%
vocal 2
 
6.1%
instrumental 1
 
3.0%
303 1
 
3.0%
eisenberg 1
 
3.0%
s 1
 
3.0%
herbert 1
 
3.0%
239 1
 
3.0%
Other values (16) 16
48.5%
2023-12-09T22:40:24.546324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
14.0%
a 16
 
7.7%
r 12
 
5.8%
e 12
 
5.8%
. 10
 
4.8%
g 8
 
3.9%
n 8
 
3.9%
o 7
 
3.4%
) 7
 
3.4%
( 7
 
3.4%
Other values (34) 91
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 109
52.7%
Uppercase Letter 32
 
15.5%
Space Separator 29
 
14.0%
Other Punctuation 11
 
5.3%
Decimal Number 11
 
5.3%
Close Punctuation 7
 
3.4%
Open Punctuation 7
 
3.4%
Dash Punctuation 1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 16
14.7%
r 12
11.0%
e 12
11.0%
g 8
 
7.3%
n 8
 
7.3%
o 7
 
6.4%
t 5
 
4.6%
m 5
 
4.6%
i 5
 
4.6%
d 4
 
3.7%
Other values (10) 27
24.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
15.6%
I 5
15.6%
M 4
12.5%
P 3
9.4%
V 2
 
6.2%
T 2
 
6.2%
D 2
 
6.2%
H 2
 
6.2%
B 2
 
6.2%
A 2
 
6.2%
Other values (3) 3
9.4%
Decimal Number
ValueCountFrequency (%)
3 3
27.3%
2 3
27.3%
9 2
18.2%
8 2
18.2%
0 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 10
90.9%
: 1
 
9.1%
Space Separator
ValueCountFrequency (%)
29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 141
68.1%
Common 66
31.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 16
 
11.3%
r 12
 
8.5%
e 12
 
8.5%
g 8
 
5.7%
n 8
 
5.7%
o 7
 
5.0%
t 5
 
3.5%
S 5
 
3.5%
m 5
 
3.5%
I 5
 
3.5%
Other values (23) 58
41.1%
Common
ValueCountFrequency (%)
29
43.9%
. 10
 
15.2%
) 7
 
10.6%
( 7
 
10.6%
3 3
 
4.5%
2 3
 
4.5%
9 2
 
3.0%
8 2
 
3.0%
: 1
 
1.5%
- 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 207
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
 
14.0%
a 16
 
7.7%
r 12
 
5.8%
e 12
 
5.8%
. 10
 
4.8%
g 8
 
3.9%
n 8
 
3.9%
o 7
 
3.4%
) 7
 
3.4%
( 7
 
3.4%
Other values (34) 91
44.0%

admissionsmethod_prog10
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.1 KiB
2023-12-09T22:40:24.715117image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length18
Median length11
Mean length12.75
Min length11

Characters and Unicode

Total characters51
Distinct characters16
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rowTalent Test
2nd rowScreened: Language
3rd rowTalent Test
4th rowTalent Test
ValueCountFrequency (%)
talent 3
37.5%
test 3
37.5%
screened 1
 
12.5%
language 1
 
12.5%
2023-12-09T22:40:25.003302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 10
19.6%
T 6
11.8%
t 6
11.8%
a 5
9.8%
n 5
9.8%
4
 
7.8%
l 3
 
5.9%
s 3
 
5.9%
g 2
 
3.9%
S 1
 
2.0%
Other values (6) 6
11.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 38
74.5%
Uppercase Letter 8
 
15.7%
Space Separator 4
 
7.8%
Other Punctuation 1
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10
26.3%
t 6
15.8%
a 5
13.2%
n 5
13.2%
l 3
 
7.9%
s 3
 
7.9%
g 2
 
5.3%
c 1
 
2.6%
r 1
 
2.6%
d 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
T 6
75.0%
S 1
 
12.5%
L 1
 
12.5%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46
90.2%
Common 5
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10
21.7%
T 6
13.0%
t 6
13.0%
a 5
10.9%
n 5
10.9%
l 3
 
6.5%
s 3
 
6.5%
g 2
 
4.3%
S 1
 
2.2%
c 1
 
2.2%
Other values (4) 4
 
8.7%
Common
ValueCountFrequency (%)
4
80.0%
: 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 10
19.6%
T 6
11.8%
t 6
11.8%
a 5
9.8%
n 5
9.8%
4
 
7.8%
l 3
 
5.9%
s 3
 
5.9%
g 2
 
3.9%
S 1
 
2.0%
Other values (6) 6
11.8%

geapps_prog10
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:25.175293image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.25
Min length2

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row57
2nd row47
3rd row355
4th row35
ValueCountFrequency (%)
47 1
25.0%
35 1
25.0%
57 1
25.0%
355 1
25.0%
2023-12-09T22:40:25.465268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 4
44.4%
7 2
22.2%
3 2
22.2%
4 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 4
44.4%
7 2
22.2%
3 2
22.2%
4 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Common 9
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 4
44.4%
7 2
22.2%
3 2
22.2%
4 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 4
44.4%
7 2
22.2%
3 2
22.2%
4 1
 
11.1%

swdapps_prog10
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:25.574393image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.25
Min length1

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row5
2nd row5
3rd row31
4th row4
ValueCountFrequency (%)
5 2
50.0%
31 1
25.0%
4 1
25.0%
2023-12-09T22:40:25.796732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2
40.0%
3 1
20.0%
1 1
20.0%
4 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2
40.0%
3 1
20.0%
1 1
20.0%
4 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2
40.0%
3 1
20.0%
1 1
20.0%
4 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2
40.0%
3 1
20.0%
1 1
20.0%
4 1
20.0%

geseats_prog10
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:25.955339image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters8
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row34
2nd row12
3rd row28
4th row22
ValueCountFrequency (%)
22 1
25.0%
12 1
25.0%
34 1
25.0%
28 1
25.0%
2023-12-09T22:40:26.221458image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
4 1
 
12.5%
8 1
 
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
4 1
 
12.5%
8 1
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
Common 8
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
4 1
 
12.5%
8 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 4
50.0%
1 1
 
12.5%
3 1
 
12.5%
4 1
 
12.5%
8 1
 
12.5%

swdseats_prog10
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:26.363074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row9
2nd row3
3rd row0
4th row6
ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
9 1
25.0%
3 1
25.0%
2023-12-09T22:40:26.621551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
9 1
25.0%
3 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
9 1
25.0%
3 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
9 1
25.0%
3 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
25.0%
0 1
25.0%
9 1
25.0%
3 1
25.0%

geappsperseat_prog10
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:26.740201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.25
Min length1

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row2
2nd row4
3rd row13
4th row2
ValueCountFrequency (%)
2 2
50.0%
13 1
25.0%
4 1
25.0%
2023-12-09T22:40:26.978990image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
3 1
20.0%
4 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
3 1
20.0%
4 1
20.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
3 1
20.0%
4 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
40.0%
1 1
20.0%
3 1
20.0%
4 1
20.0%

swdappsperseat_prog10
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing471
Missing (%)99.4%
Memory size15.0 KiB
2023-12-09T22:40:27.090342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row1
2nd row2
3rd row1
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
2023-12-09T22:40:27.322742image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%

gefilled_prog10
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:27.427837image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row0
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%
2023-12-09T22:40:27.639494image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

swdfilled_prog10
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing470
Missing (%)99.2%
Memory size15.0 KiB
2023-12-09T22:40:27.744983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row0
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%
2023-12-09T22:40:27.963289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
50.0%
0 2
50.0%

prefnote_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog10
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.2 KiB
2023-12-09T22:40:28.150841image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length43.5
Mean length40.75
Min length31

Characters and Unicode

Total characters163
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to students and residents of Brooklyn
3rd rowOpen to New York City residents
4th rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 4
13.8%
to 4
13.8%
residents 4
13.8%
students 3
10.3%
and 3
10.3%
of 3
10.3%
district 2
6.9%
21 2
6.9%
brooklyn 1
 
3.4%
new 1
 
3.4%
Other values (2) 2
6.9%
2023-12-09T22:40:28.475130image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
15.3%
t 19
11.7%
e 16
9.8%
s 16
9.8%
n 15
9.2%
o 10
 
6.1%
d 10
 
6.1%
i 9
 
5.5%
r 8
 
4.9%
O 4
 
2.5%
Other values (16) 31
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 124
76.1%
Space Separator 25
 
15.3%
Uppercase Letter 10
 
6.1%
Decimal Number 4
 
2.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 19
15.3%
e 16
12.9%
s 16
12.9%
n 15
12.1%
o 10
8.1%
d 10
8.1%
i 9
7.3%
r 8
6.5%
p 4
 
3.2%
f 3
 
2.4%
Other values (7) 14
11.3%
Uppercase Letter
ValueCountFrequency (%)
O 4
40.0%
D 2
20.0%
B 1
 
10.0%
N 1
 
10.0%
Y 1
 
10.0%
C 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 134
82.2%
Common 29
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 19
14.2%
e 16
11.9%
s 16
11.9%
n 15
11.2%
o 10
7.5%
d 10
7.5%
i 9
 
6.7%
r 8
 
6.0%
O 4
 
3.0%
p 4
 
3.0%
Other values (13) 23
17.2%
Common
ValueCountFrequency (%)
25
86.2%
2 2
 
6.9%
1 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 163
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
15.3%
t 19
11.7%
e 16
9.8%
s 16
9.8%
n 15
9.2%
o 10
 
6.1%
d 10
 
6.1%
i 9
 
5.5%
r 8
 
4.9%
O 4
 
2.5%
Other values (16) 31
19.0%

selectioncriteria1_prog10
Text

MISSING 

Distinct3
Distinct (%)75.0%
Missing470
Missing (%)99.2%
Memory size15.4 KiB
2023-12-09T22:40:28.698265image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length111.5
Mean length86.75
Min length18

Characters and Unicode

Total characters347
Distinct characters31
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd rowOn-Site Assessment
3rd rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
4th rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 6
 
10.0%
students 3
 
5.0%
based 3
 
5.0%
tests 3
 
5.0%
talent 3
 
5.0%
21 3
 
5.0%
the 3
 
5.0%
score 3
 
5.0%
who 3
 
5.0%
their 3
 
5.0%
Other values (12) 27
45.0%
2023-12-09T22:40:29.042634image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
16.1%
e 42
12.1%
t 35
 
10.1%
s 31
 
8.9%
o 18
 
5.2%
r 16
 
4.6%
n 15
 
4.3%
l 15
 
4.3%
i 14
 
4.0%
a 14
 
4.0%
Other values (21) 91
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 266
76.7%
Space Separator 56
 
16.1%
Uppercase Letter 17
 
4.9%
Decimal Number 6
 
1.7%
Dash Punctuation 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 42
15.8%
t 35
13.2%
s 31
11.7%
o 18
 
6.8%
r 16
 
6.0%
n 15
 
5.6%
l 15
 
5.6%
i 14
 
5.3%
a 14
 
5.3%
h 12
 
4.5%
Other values (10) 54
20.3%
Uppercase Letter
ValueCountFrequency (%)
T 7
41.2%
S 4
23.5%
D 3
17.6%
O 1
 
5.9%
A 1
 
5.9%
M 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 283
81.6%
Common 64
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 42
14.8%
t 35
12.4%
s 31
11.0%
o 18
 
6.4%
r 16
 
5.7%
n 15
 
5.3%
l 15
 
5.3%
i 14
 
4.9%
a 14
 
4.9%
h 12
 
4.2%
Other values (16) 71
25.1%
Common
ValueCountFrequency (%)
56
87.5%
2 3
 
4.7%
1 3
 
4.7%
- 1
 
1.6%
/ 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 347
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
16.1%
e 42
12.1%
t 35
 
10.1%
s 31
 
8.9%
o 18
 
5.2%
r 16
 
4.6%
n 15
 
4.3%
l 15
 
4.3%
i 14
 
4.0%
a 14
 
4.0%
Other values (21) 91
26.2%

selectioncriteria2_prog10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:29.253776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowwe do not test for this program anymore
ValueCountFrequency (%)
we 1
12.5%
do 1
12.5%
not 1
12.5%
test 1
12.5%
for 1
12.5%
this 1
12.5%
program 1
12.5%
anymore 1
12.5%
2023-12-09T22:40:29.568198image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
17.9%
o 5
12.8%
t 4
10.3%
r 4
10.3%
e 3
7.7%
m 2
 
5.1%
n 2
 
5.1%
s 2
 
5.1%
a 2
 
5.1%
w 1
 
2.6%
Other values (7) 7
17.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 32
82.1%
Space Separator 7
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5
15.6%
t 4
12.5%
r 4
12.5%
e 3
9.4%
m 2
 
6.2%
n 2
 
6.2%
s 2
 
6.2%
a 2
 
6.2%
w 1
 
3.1%
p 1
 
3.1%
Other values (6) 6
18.8%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 32
82.1%
Common 7
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 5
15.6%
t 4
12.5%
r 4
12.5%
e 3
9.4%
m 2
 
6.2%
n 2
 
6.2%
s 2
 
6.2%
a 2
 
6.2%
w 1
 
3.1%
p 1
 
3.1%
Other values (6) 6
18.8%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
17.9%
o 5
12.8%
t 4
10.3%
r 4
10.3%
e 3
7.7%
m 2
 
5.1%
n 2
 
5.1%
s 2
 
5.1%
a 2
 
5.1%
w 1
 
2.6%
Other values (7) 7
17.9%

selectioncriteria3_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:29.725170image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters12
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowK228SC
2nd rowK239WI
ValueCountFrequency (%)
k239wi 1
50.0%
k228sc 1
50.0%
2023-12-09T22:40:29.985554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 3
25.0%
K 2
16.7%
3 1
 
8.3%
9 1
 
8.3%
W 1
 
8.3%
I 1
 
8.3%
8 1
 
8.3%
S 1
 
8.3%
C 1
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
50.0%
Uppercase Letter 6
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 2
33.3%
W 1
16.7%
I 1
16.7%
S 1
16.7%
C 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
3 1
 
16.7%
9 1
 
16.7%
8 1
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
50.0%
Latin 6
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 2
33.3%
W 1
16.7%
I 1
16.7%
S 1
16.7%
C 1
16.7%
Common
ValueCountFrequency (%)
2 3
50.0%
3 1
 
16.7%
9 1
 
16.7%
8 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 3
25.0%
K 2
16.7%
3 1
 
8.3%
9 1
 
8.3%
W 1
 
8.3%
I 1
 
8.3%
8 1
 
8.3%
S 1
 
8.3%
C 1
 
8.3%

name_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.1 KiB
2023-12-09T22:40:30.173487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length50
Median length45
Mean length45
Min length40

Characters and Unicode

Total characters90
Distinct characters34
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Science)
2nd rowMark Twain (I.S. 239) (Wind Instruments)
ValueCountFrequency (%)
i.s 2
14.3%
mark 1
 
7.1%
twain 1
 
7.1%
239 1
 
7.1%
wind 1
 
7.1%
instruments 1
 
7.1%
david 1
 
7.1%
a 1
 
7.1%
boody 1
 
7.1%
228 1
 
7.1%
Other values (3) 3
21.4%
2023-12-09T22:40:30.488850image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
13.3%
n 6
 
6.7%
a 5
 
5.6%
. 5
 
5.6%
( 4
 
4.4%
r 4
 
4.4%
) 4
 
4.4%
e 4
 
4.4%
i 4
 
4.4%
S 3
 
3.3%
Other values (24) 39
43.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 45
50.0%
Uppercase Letter 14
 
15.6%
Space Separator 12
 
13.3%
Decimal Number 6
 
6.7%
Other Punctuation 5
 
5.6%
Open Punctuation 4
 
4.4%
Close Punctuation 4
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 6
13.3%
a 5
11.1%
r 4
8.9%
e 4
8.9%
i 4
8.9%
t 3
 
6.7%
d 3
 
6.7%
o 3
 
6.7%
m 2
 
4.4%
s 2
 
4.4%
Other values (7) 9
20.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
21.4%
I 3
21.4%
M 2
14.3%
D 1
 
7.1%
A 1
 
7.1%
B 1
 
7.1%
T 1
 
7.1%
P 1
 
7.1%
W 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
9 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 59
65.6%
Common 31
34.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 6
 
10.2%
a 5
 
8.5%
r 4
 
6.8%
e 4
 
6.8%
i 4
 
6.8%
S 3
 
5.1%
t 3
 
5.1%
d 3
 
5.1%
I 3
 
5.1%
o 3
 
5.1%
Other values (16) 21
35.6%
Common
ValueCountFrequency (%)
12
38.7%
. 5
16.1%
( 4
 
12.9%
) 4
 
12.9%
2 3
 
9.7%
9 1
 
3.2%
3 1
 
3.2%
8 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 90
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
 
13.3%
n 6
 
6.7%
a 5
 
5.6%
. 5
 
5.6%
( 4
 
4.4%
r 4
 
4.4%
) 4
 
4.4%
e 4
 
4.4%
i 4
 
4.4%
S 3
 
3.3%
Other values (24) 39
43.3%

admissionsmethod_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:30.642827image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters22
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTalent Test
2nd rowTalent Test
ValueCountFrequency (%)
talent 2
50.0%
test 2
50.0%
2023-12-09T22:40:30.894105image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 4
18.2%
e 4
18.2%
t 4
18.2%
a 2
9.1%
l 2
9.1%
n 2
9.1%
2
9.1%
s 2
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
72.7%
Uppercase Letter 4
 
18.2%
Space Separator 2
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
t 4
25.0%
a 2
12.5%
l 2
12.5%
n 2
12.5%
s 2
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
90.9%
Common 2
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 4
20.0%
e 4
20.0%
t 4
20.0%
a 2
10.0%
l 2
10.0%
n 2
10.0%
s 2
10.0%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 4
18.2%
e 4
18.2%
t 4
18.2%
a 2
9.1%
l 2
9.1%
n 2
9.1%
2
9.1%
s 2
9.1%

geapps_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:31.049839image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row357
2nd row200
ValueCountFrequency (%)
200 1
50.0%
357 1
50.0%
2023-12-09T22:40:31.316228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
3 1
16.7%
5 1
16.7%
7 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
3 1
16.7%
5 1
16.7%
7 1
16.7%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
3 1
16.7%
5 1
16.7%
7 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
33.3%
2 1
16.7%
3 1
16.7%
5 1
16.7%
7 1
16.7%

swdapps_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:31.466514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row27
2nd row10
ValueCountFrequency (%)
10 1
50.0%
27 1
50.0%
2023-12-09T22:40:31.724101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
25.0%
0 1
25.0%
2 1
25.0%
7 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
25.0%
0 1
25.0%
2 1
25.0%
7 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
25.0%
0 1
25.0%
2 1
25.0%
7 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
25.0%
0 1
25.0%
2 1
25.0%
7 1
25.0%

geseats_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:31.874728image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row26
2nd row25
ValueCountFrequency (%)
25 1
50.0%
26 1
50.0%
2023-12-09T22:40:32.133084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
6 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
6 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
6 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
6 1
25.0%

swdseats_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:32.240350image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
ValueCountFrequency (%)
7 2
100.0%
2023-12-09T22:40:32.445526image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 2
100.0%

geappsperseat_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:32.575550image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length1.5
Mean length1.5
Min length1

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row14
2nd row8
ValueCountFrequency (%)
14 1
50.0%
8 1
50.0%
2023-12-09T22:40:32.819365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
8 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
33.3%
4 1
33.3%
8 1
33.3%

swdappsperseat_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:32.924392image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row4
2nd row1
ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%
2023-12-09T22:40:33.131793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
4 1
50.0%

gefilled_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:33.231476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
ValueCountFrequency (%)
1 2
100.0%
2023-12-09T22:40:33.436546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
100.0%

swdfilled_prog11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing472
Missing (%)99.6%
Memory size15.0 KiB
2023-12-09T22:40:33.535360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
ValueCountFrequency (%)
0 2
100.0%
2023-12-09T22:40:33.742372image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
100.0%

prefnote_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.1 KiB
2023-12-09T22:40:33.938032image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length38
Mean length38
Min length31

Characters and Unicode

Total characters76
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
2nd rowOpen to New York City residents
ValueCountFrequency (%)
open 2
14.3%
to 2
14.3%
residents 2
14.3%
students 1
7.1%
and 1
7.1%
of 1
7.1%
district 1
7.1%
21 1
7.1%
new 1
7.1%
york 1
7.1%
2023-12-09T22:40:34.252033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
15.8%
t 9
11.8%
e 8
10.5%
s 7
9.2%
n 6
 
7.9%
i 5
 
6.6%
r 4
 
5.3%
o 4
 
5.3%
d 4
 
5.3%
p 2
 
2.6%
Other values (14) 15
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 56
73.7%
Space Separator 12
 
15.8%
Uppercase Letter 6
 
7.9%
Decimal Number 2
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 9
16.1%
e 8
14.3%
s 7
12.5%
n 6
10.7%
i 5
8.9%
r 4
7.1%
o 4
7.1%
d 4
7.1%
p 2
 
3.6%
a 1
 
1.8%
Other values (6) 6
10.7%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
D 1
16.7%
N 1
16.7%
Y 1
16.7%
C 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 62
81.6%
Common 14
 
18.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 9
14.5%
e 8
12.9%
s 7
11.3%
n 6
9.7%
i 5
8.1%
r 4
 
6.5%
o 4
 
6.5%
d 4
 
6.5%
p 2
 
3.2%
O 2
 
3.2%
Other values (11) 11
17.7%
Common
ValueCountFrequency (%)
12
85.7%
2 1
 
7.1%
1 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
15.8%
t 9
11.8%
e 8
10.5%
s 7
9.2%
n 6
 
7.9%
i 5
 
6.6%
r 4
 
5.3%
o 4
 
5.3%
d 4
 
5.3%
p 2
 
2.6%
Other values (14) 15
19.7%

selectioncriteria1_prog11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing472
Missing (%)99.6%
Memory size15.2 KiB
2023-12-09T22:40:34.454717image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length117
Median length111.5
Mean length111.5
Min length106

Characters and Unicode

Total characters223
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
2nd rowStudents who apply to these programs will be selected based on their score on the Mark Twain/District 21 Talent Tests
ValueCountFrequency (%)
on 4
 
10.3%
based 2
 
5.1%
tests 2
 
5.1%
talent 2
 
5.1%
21 2
 
5.1%
the 2
 
5.1%
score 2
 
5.1%
their 2
 
5.1%
who 2
 
5.1%
students 2
 
5.1%
Other values (10) 17
43.6%
2023-12-09T22:40:34.770094image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
37
16.6%
e 26
11.7%
t 22
 
9.9%
s 18
 
8.1%
o 12
 
5.4%
r 11
 
4.9%
l 10
 
4.5%
a 10
 
4.5%
i 9
 
4.0%
n 9
 
4.0%
Other values (18) 59
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 171
76.7%
Space Separator 37
 
16.6%
Uppercase Letter 10
 
4.5%
Decimal Number 4
 
1.8%
Other Punctuation 1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 26
15.2%
t 22
12.9%
s 18
10.5%
o 12
 
7.0%
r 11
 
6.4%
l 10
 
5.8%
a 10
 
5.8%
i 9
 
5.3%
n 9
 
5.3%
h 8
 
4.7%
Other values (10) 36
21.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
50.0%
D 2
 
20.0%
S 2
 
20.0%
M 1
 
10.0%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%
Space Separator
ValueCountFrequency (%)
37
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 181
81.2%
Common 42
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 26
14.4%
t 22
12.2%
s 18
 
9.9%
o 12
 
6.6%
r 11
 
6.1%
l 10
 
5.5%
a 10
 
5.5%
i 9
 
5.0%
n 9
 
5.0%
h 8
 
4.4%
Other values (14) 46
25.4%
Common
ValueCountFrequency (%)
37
88.1%
1 2
 
4.8%
2 2
 
4.8%
/ 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
37
16.6%
e 26
11.7%
t 22
 
9.9%
s 18
 
8.1%
o 12
 
5.4%
r 11
 
4.9%
l 10
 
4.5%
a 10
 
4.5%
i 9
 
4.0%
n 9
 
4.0%
Other values (18) 59
26.5%

selectioncriteria2_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:34.921264image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228ST
ValueCountFrequency (%)
k228st 1
100.0%
2023-12-09T22:40:35.172112image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
S 1
16.7%
T 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
T 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
S 1
33.3%
T 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
S 1
16.7%
T 1
16.7%

name_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:35.360820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters63
Distinct characters29
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Instrumental-Strings)
ValueCountFrequency (%)
david 1
12.5%
a 1
12.5%
boody 1
12.5%
i.s 1
12.5%
228 1
12.5%
magnet 1
12.5%
program 1
12.5%
instrumental-strings 1
12.5%
2023-12-09T22:40:35.665270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
 
11.1%
n 4
 
6.3%
r 4
 
6.3%
a 4
 
6.3%
t 4
 
6.3%
g 3
 
4.8%
. 3
 
4.8%
o 3
 
4.8%
2 2
 
3.2%
I 2
 
3.2%
Other values (19) 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 36
57.1%
Uppercase Letter 9
 
14.3%
Space Separator 7
 
11.1%
Other Punctuation 3
 
4.8%
Decimal Number 3
 
4.8%
Close Punctuation 2
 
3.2%
Open Punctuation 2
 
3.2%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4
11.1%
r 4
11.1%
a 4
11.1%
t 4
11.1%
g 3
8.3%
o 3
8.3%
m 2
 
5.6%
s 2
 
5.6%
d 2
 
5.6%
i 2
 
5.6%
Other values (5) 6
16.7%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
S 2
22.2%
P 1
11.1%
D 1
11.1%
M 1
11.1%
B 1
11.1%
A 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45
71.4%
Common 18
 
28.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
 
8.9%
r 4
 
8.9%
a 4
 
8.9%
t 4
 
8.9%
g 3
 
6.7%
o 3
 
6.7%
I 2
 
4.4%
S 2
 
4.4%
m 2
 
4.4%
s 2
 
4.4%
Other values (12) 15
33.3%
Common
ValueCountFrequency (%)
7
38.9%
. 3
16.7%
2 2
 
11.1%
) 2
 
11.1%
( 2
 
11.1%
8 1
 
5.6%
- 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
 
11.1%
n 4
 
6.3%
r 4
 
6.3%
a 4
 
6.3%
t 4
 
6.3%
g 3
 
4.8%
. 3
 
4.8%
o 3
 
4.8%
2 2
 
3.2%
I 2
 
3.2%
Other values (19) 27
42.9%

admissionsmethod_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:35.814762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:40:37.187237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:37.295553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row58
ValueCountFrequency (%)
58 1
100.0%
2023-12-09T22:40:37.508381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1
50.0%
8 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1
50.0%
8 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1
50.0%
8 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1
50.0%
8 1
50.0%

swdapps_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:37.610866image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row6
ValueCountFrequency (%)
6 1
100.0%
2023-12-09T22:40:37.821720image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
100.0%

geseats_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:37.923367image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row16
ValueCountFrequency (%)
16 1
100.0%
2023-12-09T22:40:38.136877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

swdseats_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:38.238219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:40:38.452883image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

geappsperseat_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:38.555441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:40:38.765665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

swdappsperseat_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:38.867473image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:40:39.085150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

gefilled_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:39.187018image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:39.394245image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

swdfilled_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:39.493965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:39.703218image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

prefnote_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:39.886166image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:40:40.209348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

selectioncriteria1_prog12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.1 KiB
2023-12-09T22:40:40.413256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length106
Median length106
Mean length106
Min length106

Characters and Unicode

Total characters106
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 2
 
10.5%
students 1
 
5.3%
who 1
 
5.3%
talent 1
 
5.3%
21 1
 
5.3%
district 1
 
5.3%
the 1
 
5.3%
score 1
 
5.3%
their 1
 
5.3%
based 1
 
5.3%
Other values (8) 8
42.1%
2023-12-09T22:40:40.732712image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
77.4%
Space Separator 18
 
17.0%
Uppercase Letter 4
 
3.8%
Decimal Number 2
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
15.9%
t 11
13.4%
s 9
11.0%
o 6
 
7.3%
r 5
 
6.1%
l 5
 
6.1%
n 4
 
4.9%
h 4
 
4.9%
a 4
 
4.9%
i 4
 
4.9%
Other values (9) 17
20.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
D 1
25.0%
S 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86
81.1%
Common 20
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
15.1%
t 11
12.8%
s 9
10.5%
o 6
 
7.0%
r 5
 
5.8%
l 5
 
5.8%
n 4
 
4.7%
h 4
 
4.7%
a 4
 
4.7%
i 4
 
4.7%
Other values (12) 21
24.4%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
1 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

selectioncriteria2_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:40.883404image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228VO
ValueCountFrequency (%)
k228vo 1
100.0%
2023-12-09T22:40:41.136940image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
V 1
16.7%
O 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
V 1
33.3%
O 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
V 1
33.3%
O 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
V 1
16.7%
O 1
16.7%

name_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:41.320965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length54
Median length54
Mean length54
Min length54

Characters and Unicode

Total characters54
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Vocal Music)
ValueCountFrequency (%)
david 1
11.1%
a 1
11.1%
boody 1
11.1%
i.s 1
11.1%
228 1
11.1%
magnet 1
11.1%
program 1
11.1%
vocal 1
11.1%
music 1
11.1%
2023-12-09T22:40:41.621595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
 
14.8%
o 4
 
7.4%
a 4
 
7.4%
. 3
 
5.6%
2 2
 
3.7%
g 2
 
3.7%
i 2
 
3.7%
d 2
 
3.7%
M 2
 
3.7%
c 2
 
3.7%
Other values (20) 23
42.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27
50.0%
Uppercase Letter 9
 
16.7%
Space Separator 8
 
14.8%
Other Punctuation 3
 
5.6%
Decimal Number 3
 
5.6%
Close Punctuation 2
 
3.7%
Open Punctuation 2
 
3.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
14.8%
a 4
14.8%
g 2
 
7.4%
i 2
 
7.4%
d 2
 
7.4%
c 2
 
7.4%
r 2
 
7.4%
m 1
 
3.7%
t 1
 
3.7%
l 1
 
3.7%
Other values (6) 6
22.2%
Uppercase Letter
ValueCountFrequency (%)
M 2
22.2%
D 1
11.1%
V 1
11.1%
P 1
11.1%
S 1
11.1%
I 1
11.1%
B 1
11.1%
A 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
66.7%
Common 18
33.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
 
11.1%
a 4
 
11.1%
g 2
 
5.6%
i 2
 
5.6%
d 2
 
5.6%
M 2
 
5.6%
c 2
 
5.6%
r 2
 
5.6%
D 1
 
2.8%
V 1
 
2.8%
Other values (14) 14
38.9%
Common
ValueCountFrequency (%)
8
44.4%
. 3
 
16.7%
2 2
 
11.1%
) 2
 
11.1%
( 2
 
11.1%
8 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8
 
14.8%
o 4
 
7.4%
a 4
 
7.4%
. 3
 
5.6%
2 2
 
3.7%
g 2
 
3.7%
i 2
 
3.7%
d 2
 
3.7%
M 2
 
3.7%
c 2
 
3.7%
Other values (20) 23
42.6%

admissionsmethod_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:41.771005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:40:42.026750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:42.129057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row93
ValueCountFrequency (%)
93 1
100.0%
2023-12-09T22:40:42.350477image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1
50.0%
3 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 1
50.0%
3 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 1
50.0%
3 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 1
50.0%
3 1
50.0%

swdapps_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:42.457970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row17
ValueCountFrequency (%)
17 1
100.0%
2023-12-09T22:40:42.679353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
7 1
50.0%

geseats_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:42.785443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row8
ValueCountFrequency (%)
8 1
100.0%
2023-12-09T22:40:43.004849image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 1
100.0%

swdseats_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:43.109043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:40:43.317054image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

geappsperseat_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:43.417784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row12
ValueCountFrequency (%)
12 1
100.0%
2023-12-09T22:40:43.625219image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

swdappsperseat_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:43.724120image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row9
ValueCountFrequency (%)
9 1
100.0%
2023-12-09T22:40:43.931085image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 1
100.0%

gefilled_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:44.030488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1
ValueCountFrequency (%)
1 1
100.0%
2023-12-09T22:40:44.241962image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
100.0%

swdfilled_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:44.343613image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1
ValueCountFrequency (%)
1 1
100.0%
2023-12-09T22:40:44.553596image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
100.0%

prefnote_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:44.734289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:40:45.028249image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

selectioncriteria1_prog13
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.1 KiB
2023-12-09T22:40:45.222182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length106
Median length106
Mean length106
Min length106

Characters and Unicode

Total characters106
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 2
 
10.5%
students 1
 
5.3%
who 1
 
5.3%
talent 1
 
5.3%
21 1
 
5.3%
district 1
 
5.3%
the 1
 
5.3%
score 1
 
5.3%
their 1
 
5.3%
based 1
 
5.3%
Other values (8) 8
42.1%
2023-12-09T22:40:45.528879image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
77.4%
Space Separator 18
 
17.0%
Uppercase Letter 4
 
3.8%
Decimal Number 2
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
15.9%
t 11
13.4%
s 9
11.0%
o 6
 
7.3%
r 5
 
6.1%
l 5
 
6.1%
n 4
 
4.9%
h 4
 
4.9%
a 4
 
4.9%
i 4
 
4.9%
Other values (9) 17
20.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
D 1
25.0%
S 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86
81.1%
Common 20
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
15.1%
t 11
12.8%
s 9
10.5%
o 6
 
7.0%
r 5
 
5.8%
l 5
 
5.8%
n 4
 
4.7%
h 4
 
4.7%
a 4
 
4.7%
i 4
 
4.7%
Other values (12) 21
24.4%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
1 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

selectioncriteria2_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:45.679204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters6
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228WI
ValueCountFrequency (%)
k228wi 1
100.0%
2023-12-09T22:40:45.929197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
W 1
16.7%
I 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
50.0%
Uppercase Letter 3
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
W 1
33.3%
I 1
33.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
50.0%
Latin 3
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
K 1
33.3%
W 1
33.3%
I 1
33.3%
Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
33.3%
K 1
16.7%
8 1
16.7%
W 1
16.7%
I 1
16.7%

name_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:46.113318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters63
Distinct characters30
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Magnet Program (Instrumental - Winds)
ValueCountFrequency (%)
david 1
10.0%
a 1
10.0%
boody 1
10.0%
i.s 1
10.0%
228 1
10.0%
magnet 1
10.0%
program 1
10.0%
instrumental 1
10.0%
1
10.0%
winds 1
10.0%
2023-12-09T22:40:46.418848image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9
 
14.3%
n 4
 
6.3%
a 4
 
6.3%
t 3
 
4.8%
d 3
 
4.8%
. 3
 
4.8%
r 3
 
4.8%
o 3
 
4.8%
m 2
 
3.2%
e 2
 
3.2%
Other values (20) 27
42.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
54.0%
Space Separator 9
 
14.3%
Uppercase Letter 9
 
14.3%
Other Punctuation 3
 
4.8%
Decimal Number 3
 
4.8%
Close Punctuation 2
 
3.2%
Open Punctuation 2
 
3.2%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 4
11.8%
a 4
11.8%
t 3
8.8%
d 3
8.8%
r 3
8.8%
o 3
8.8%
m 2
 
5.9%
e 2
 
5.9%
g 2
 
5.9%
s 2
 
5.9%
Other values (5) 6
17.6%
Uppercase Letter
ValueCountFrequency (%)
I 2
22.2%
P 1
11.1%
D 1
11.1%
M 1
11.1%
S 1
11.1%
B 1
11.1%
A 1
11.1%
W 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43
68.3%
Common 20
31.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 4
 
9.3%
a 4
 
9.3%
t 3
 
7.0%
d 3
 
7.0%
r 3
 
7.0%
o 3
 
7.0%
m 2
 
4.7%
e 2
 
4.7%
g 2
 
4.7%
I 2
 
4.7%
Other values (13) 15
34.9%
Common
ValueCountFrequency (%)
9
45.0%
. 3
 
15.0%
) 2
 
10.0%
2 2
 
10.0%
( 2
 
10.0%
- 1
 
5.0%
8 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9
 
14.3%
n 4
 
6.3%
a 4
 
6.3%
t 3
 
4.8%
d 3
 
4.8%
. 3
 
4.8%
r 3
 
4.8%
o 3
 
4.8%
m 2
 
3.2%
e 2
 
3.2%
Other values (20) 27
42.9%

admissionsmethod_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:46.568206image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters11
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowTalent Test
ValueCountFrequency (%)
talent 1
50.0%
test 1
50.0%
2023-12-09T22:40:46.830133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
72.7%
Uppercase Letter 2
 
18.2%
Space Separator 1
 
9.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
t 2
25.0%
a 1
12.5%
l 1
12.5%
n 1
12.5%
s 1
12.5%
Uppercase Letter
ValueCountFrequency (%)
T 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10
90.9%
Common 1
 
9.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
T 2
20.0%
e 2
20.0%
t 2
20.0%
a 1
10.0%
l 1
10.0%
n 1
10.0%
s 1
10.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
T 2
18.2%
e 2
18.2%
t 2
18.2%
a 1
9.1%
l 1
9.1%
n 1
9.1%
1
9.1%
s 1
9.1%

geapps_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:46.934121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row42
ValueCountFrequency (%)
42 1
100.0%
2023-12-09T22:40:47.143156image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
50.0%
2 1
50.0%

swdapps_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:47.244216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row6
ValueCountFrequency (%)
6 1
100.0%
2023-12-09T22:40:47.457397image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 1
100.0%

geseats_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:47.557870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row16
ValueCountFrequency (%)
16 1
100.0%
2023-12-09T22:40:47.766754image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1
50.0%
6 1
50.0%

swdseats_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:47.866758image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row4
ValueCountFrequency (%)
4 1
100.0%
2023-12-09T22:40:48.072332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
100.0%

geappsperseat_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:48.171509image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row3
ValueCountFrequency (%)
3 1
100.0%
2023-12-09T22:40:48.381294image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 1
100.0%

swdappsperseat_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:48.480903image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:40:48.688095image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

gefilled_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:48.787381image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:48.993991image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

swdfilled_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:49.096600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:49.314873image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

prefnote_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:49.582279image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters45
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students and residents of District 21
ValueCountFrequency (%)
open 1
12.5%
to 1
12.5%
students 1
12.5%
and 1
12.5%
residents 1
12.5%
of 1
12.5%
district 1
12.5%
21 1
12.5%
2023-12-09T22:40:49.879244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34
75.6%
Space Separator 7
 
15.6%
Decimal Number 2
 
4.4%
Uppercase Letter 2
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 6
17.6%
s 5
14.7%
e 4
11.8%
n 4
11.8%
d 3
8.8%
i 3
8.8%
o 2
 
5.9%
r 2
 
5.9%
f 1
 
2.9%
c 1
 
2.9%
Other values (3) 3
8.8%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 36
80.0%
Common 9
 
20.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 6
16.7%
s 5
13.9%
e 4
11.1%
n 4
11.1%
d 3
8.3%
i 3
8.3%
o 2
 
5.6%
r 2
 
5.6%
f 1
 
2.8%
c 1
 
2.8%
Other values (5) 5
13.9%
Common
ValueCountFrequency (%)
7
77.8%
2 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7
15.6%
t 6
13.3%
s 5
11.1%
e 4
8.9%
n 4
8.9%
d 3
 
6.7%
i 3
 
6.7%
o 2
 
4.4%
r 2
 
4.4%
f 1
 
2.2%
Other values (8) 8
17.8%

selectioncriteria1_prog14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.1 KiB
2023-12-09T22:40:50.075073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length106
Median length106
Mean length106
Min length106

Characters and Unicode

Total characters106
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowStudents who apply to these programs will be selected based on their score on the District 21 Talent Tests
ValueCountFrequency (%)
on 2
 
10.5%
students 1
 
5.3%
who 1
 
5.3%
talent 1
 
5.3%
21 1
 
5.3%
district 1
 
5.3%
the 1
 
5.3%
score 1
 
5.3%
their 1
 
5.3%
based 1
 
5.3%
Other values (8) 8
42.1%
2023-12-09T22:40:50.390684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82
77.4%
Space Separator 18
 
17.0%
Uppercase Letter 4
 
3.8%
Decimal Number 2
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13
15.9%
t 11
13.4%
s 9
11.0%
o 6
 
7.3%
r 5
 
6.1%
l 5
 
6.1%
n 4
 
4.9%
h 4
 
4.9%
a 4
 
4.9%
i 4
 
4.9%
Other values (9) 17
20.7%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
D 1
25.0%
S 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86
81.1%
Common 20
 
18.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13
15.1%
t 11
12.8%
s 9
10.5%
o 6
 
7.0%
r 5
 
5.8%
l 5
 
5.8%
n 4
 
4.7%
h 4
 
4.7%
a 4
 
4.7%
i 4
 
4.7%
Other values (12) 21
24.4%
Common
ValueCountFrequency (%)
18
90.0%
2 1
 
5.0%
1 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 106
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
17.0%
e 13
12.3%
t 11
10.4%
s 9
 
8.5%
o 6
 
5.7%
r 5
 
4.7%
l 5
 
4.7%
n 4
 
3.8%
h 4
 
3.8%
a 4
 
3.8%
Other values (15) 27
25.5%

selectioncriteria2_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

code_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:50.533517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters4
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowK228Z
ValueCountFrequency (%)
k228z 1
100.0%
2023-12-09T22:40:50.778983image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2
40.0%
K 1
20.0%
8 1
20.0%
Z 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
60.0%
Uppercase Letter 2
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
Z 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
60.0%
Latin 2
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
Z 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2
40.0%
K 1
20.0%
8 1
20.0%
Z 1
20.0%

name_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:50.957400image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters39
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDavid A. Boody (I.S. 228) Zoned Program
ValueCountFrequency (%)
david 1
14.3%
a 1
14.3%
boody 1
14.3%
i.s 1
14.3%
228 1
14.3%
zoned 1
14.3%
program 1
14.3%
2023-12-09T22:40:51.258797image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
15.4%
o 4
 
10.3%
d 3
 
7.7%
. 3
 
7.7%
r 2
 
5.1%
a 2
 
5.1%
2 2
 
5.1%
D 1
 
2.6%
8 1
 
2.6%
g 1
 
2.6%
Other values (14) 14
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
46.2%
Uppercase Letter 7
 
17.9%
Space Separator 6
 
15.4%
Other Punctuation 3
 
7.7%
Decimal Number 3
 
7.7%
Close Punctuation 1
 
2.6%
Open Punctuation 1
 
2.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
22.2%
d 3
16.7%
r 2
11.1%
a 2
11.1%
g 1
 
5.6%
e 1
 
5.6%
n 1
 
5.6%
y 1
 
5.6%
i 1
 
5.6%
v 1
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
D 1
14.3%
P 1
14.3%
Z 1
14.3%
I 1
14.3%
S 1
14.3%
B 1
14.3%
A 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
8 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25
64.1%
Common 14
35.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4
16.0%
d 3
 
12.0%
r 2
 
8.0%
a 2
 
8.0%
D 1
 
4.0%
g 1
 
4.0%
P 1
 
4.0%
e 1
 
4.0%
n 1
 
4.0%
Z 1
 
4.0%
Other values (8) 8
32.0%
Common
ValueCountFrequency (%)
6
42.9%
. 3
21.4%
2 2
 
14.3%
8 1
 
7.1%
) 1
 
7.1%
( 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
15.4%
o 4
 
10.3%
d 3
 
7.7%
. 3
 
7.7%
r 2
 
5.1%
a 2
 
5.1%
2 2
 
5.1%
D 1
 
2.6%
8 1
 
2.6%
g 1
 
2.6%
Other values (14) 14
35.9%

admissionsmethod_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:51.397461image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters5
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowZoned
ValueCountFrequency (%)
zoned 1
100.0%
2023-12-09T22:40:51.652150image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4
80.0%
Uppercase Letter 1
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
n 1
25.0%
e 1
25.0%
d 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
Z 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
Z 1
20.0%
o 1
20.0%
n 1
20.0%
e 1
20.0%
d 1
20.0%

geapps_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:51.764751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row177
ValueCountFrequency (%)
177 1
100.0%
2023-12-09T22:40:51.986600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 2
66.7%
1 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 2
66.7%
1 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 2
66.7%
1 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 2
66.7%
1 1
33.3%

swdapps_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:52.089375image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row48
ValueCountFrequency (%)
48 1
100.0%
2023-12-09T22:40:52.319187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 1
50.0%
8 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 1
50.0%
8 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 1
50.0%
8 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 1
50.0%
8 1
50.0%

geseats_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:52.437620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row113
ValueCountFrequency (%)
113 1
100.0%
2023-12-09T22:40:52.663888image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2
66.7%
3 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2
66.7%
3 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2
66.7%
3 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2
66.7%
3 1
33.3%

swdseats_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:52.765600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row28
ValueCountFrequency (%)
28 1
100.0%
2023-12-09T22:40:52.975009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
50.0%
8 1
50.0%

geappsperseat_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:53.075566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:40:53.286348image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

swdappsperseat_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:53.388445image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2
ValueCountFrequency (%)
2 1
100.0%
2023-12-09T22:40:53.599668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1
100.0%

gefilled_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:53.700776image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:53.909283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

swdfilled_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:54.009072image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters1
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row0
ValueCountFrequency (%)
0 1
100.0%
2023-12-09T22:40:54.222750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1
100.0%

prefnote_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority1_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority2_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority3_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority4_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority5_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority6_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

priority7_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

eligibility_prog15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing473
Missing (%)99.8%
Memory size15.0 KiB
2023-12-09T22:40:54.404768image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowOpen to students residing in the zone
ValueCountFrequency (%)
open 1
14.3%
to 1
14.3%
students 1
14.3%
residing 1
14.3%
in 1
14.3%
the 1
14.3%
zone 1
14.3%
2023-12-09T22:40:54.705191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
16.2%
e 5
13.5%
n 5
13.5%
t 4
10.8%
s 3
8.1%
i 3
8.1%
o 2
 
5.4%
d 2
 
5.4%
O 1
 
2.7%
p 1
 
2.7%
Other values (5) 5
13.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30
81.1%
Space Separator 6
 
16.2%
Uppercase Letter 1
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5
16.7%
n 5
16.7%
t 4
13.3%
s 3
10.0%
i 3
10.0%
o 2
 
6.7%
d 2
 
6.7%
p 1
 
3.3%
u 1
 
3.3%
r 1
 
3.3%
Other values (3) 3
10.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 31
83.8%
Common 6
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5
16.1%
n 5
16.1%
t 4
12.9%
s 3
9.7%
i 3
9.7%
o 2
 
6.5%
d 2
 
6.5%
O 1
 
3.2%
p 1
 
3.2%
u 1
 
3.2%
Other values (4) 4
12.9%
Common
ValueCountFrequency (%)
6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
16.2%
e 5
13.5%
n 5
13.5%
t 4
10.8%
s 3
8.1%
i 3
8.1%
o 2
 
5.4%
d 2
 
5.4%
O 1
 
2.7%
p 1
 
2.7%
Other values (5) 5
13.5%

selectioncriteria1_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria2_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria3_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria4_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria5_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria6_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria7_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

selectioncriteria8_prog15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

coursepassrate
Text

MISSING 

Distinct42
Distinct (%)9.1%
Missing10
Missing (%)2.1%
Memory size27.2 KiB
2023-12-09T22:40:54.935812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.068965517
Min length2

Characters and Unicode

Total characters960
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.4%

Sample

1st row94
2nd row77
3rd row98
4th row81
5th row99
ValueCountFrequency (%)
99 52
 
11.2%
98 42
 
9.1%
97 35
 
7.5%
96 32
 
6.9%
100 32
 
6.9%
95 30
 
6.5%
93 27
 
5.8%
94 24
 
5.2%
92 24
 
5.2%
91 20
 
4.3%
Other values (32) 146
31.5%
2023-12-09T22:40:55.292731image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 369
38.4%
8 149
15.5%
0 87
 
9.1%
7 74
 
7.7%
1 64
 
6.7%
6 59
 
6.1%
5 49
 
5.1%
3 40
 
4.2%
4 35
 
3.6%
2 34
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 960
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 369
38.4%
8 149
15.5%
0 87
 
9.1%
7 74
 
7.7%
1 64
 
6.7%
6 59
 
6.1%
5 49
 
5.1%
3 40
 
4.2%
4 35
 
3.6%
2 34
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
Common 960
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 369
38.4%
8 149
15.5%
0 87
 
9.1%
7 74
 
7.7%
1 64
 
6.7%
6 59
 
6.1%
5 49
 
5.1%
3 40
 
4.2%
4 35
 
3.6%
2 34
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 369
38.4%
8 149
15.5%
0 87
 
9.1%
7 74
 
7.7%
1 64
 
6.7%
6 59
 
6.1%
5 49
 
5.1%
3 40
 
4.2%
4 35
 
3.6%
2 34
 
3.5%

elaprof
Text

MISSING 

Distinct85
Distinct (%)18.4%
Missing13
Missing (%)2.7%
Memory size27.1 KiB
2023-12-09T22:40:55.599557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.995661605
Min length1

Characters and Unicode

Total characters920
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.0%

Sample

1st row28
2nd row28
3rd row73
4th row47
5th row24
ValueCountFrequency (%)
28 23
 
5.0%
32 15
 
3.3%
22 15
 
3.3%
56 13
 
2.8%
27 12
 
2.6%
26 12
 
2.6%
33 11
 
2.4%
40 11
 
2.4%
52 11
 
2.4%
23 11
 
2.4%
Other values (75) 327
70.9%
2023-12-09T22:40:56.035098image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 163
17.7%
3 145
15.8%
6 104
11.3%
4 101
11.0%
5 100
10.9%
1 80
8.7%
7 74
8.0%
8 66
7.2%
9 47
 
5.1%
0 40
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 920
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 163
17.7%
3 145
15.8%
6 104
11.3%
4 101
11.0%
5 100
10.9%
1 80
8.7%
7 74
8.0%
8 66
7.2%
9 47
 
5.1%
0 40
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
Common 920
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 163
17.7%
3 145
15.8%
6 104
11.3%
4 101
11.0%
5 100
10.9%
1 80
8.7%
7 74
8.0%
8 66
7.2%
9 47
 
5.1%
0 40
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 163
17.7%
3 145
15.8%
6 104
11.3%
4 101
11.0%
5 100
10.9%
1 80
8.7%
7 74
8.0%
8 66
7.2%
9 47
 
5.1%
0 40
 
4.3%

mathprof
Text

MISSING 

Distinct91
Distinct (%)19.7%
Missing13
Missing (%)2.7%
Memory size27.1 KiB
2023-12-09T22:40:56.359535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.926247289
Min length1

Characters and Unicode

Total characters888
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.0%

Sample

1st row13
2nd row19
3rd row78
4th row32
5th row12
ValueCountFrequency (%)
12 18
 
3.9%
20 15
 
3.3%
11 15
 
3.3%
28 13
 
2.8%
13 12
 
2.6%
15 12
 
2.6%
14 12
 
2.6%
16 11
 
2.4%
21 10
 
2.2%
19 10
 
2.2%
Other values (81) 333
72.2%
2023-12-09T22:40:56.802996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 166
18.7%
2 138
15.5%
3 102
11.5%
4 102
11.5%
5 99
11.1%
6 65
 
7.3%
7 61
 
6.9%
8 60
 
6.8%
9 50
 
5.6%
0 45
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 888
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 166
18.7%
2 138
15.5%
3 102
11.5%
4 102
11.5%
5 99
11.1%
6 65
 
7.3%
7 61
 
6.9%
8 60
 
6.8%
9 50
 
5.6%
0 45
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Common 888
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 166
18.7%
2 138
15.5%
3 102
11.5%
4 102
11.5%
5 99
11.1%
6 65
 
7.3%
7 61
 
6.9%
8 60
 
6.8%
9 50
 
5.6%
0 45
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 888
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 166
18.7%
2 138
15.5%
3 102
11.5%
4 102
11.5%
5 99
11.1%
6 65
 
7.3%
7 61
 
6.9%
8 60
 
6.8%
9 50
 
5.6%
0 45
 
5.1%

tophs1
Text

MISSING 

Distinct249
Distinct (%)53.9%
Missing12
Missing (%)2.5%
Memory size41.9 KiB
2023-12-09T22:40:57.185134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length88
Median length62
Mean length34.65151515
Min length11

Characters and Unicode

Total characters16009
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)34.4%

Sample

1st rowOrchard Collegiate Academy
2nd rowOrchard Collegiate Academy
3rd rowUniversity Neighborhood High School
4th rowLower Manhattan Arts Academy
5th rowPace High School
ValueCountFrequency (%)
school 374
 
15.6%
high 297
 
12.4%
for 99
 
4.1%
academy 81
 
3.4%
and 79
 
3.3%
the 51
 
2.1%
of 44
 
1.8%
arts 32
 
1.3%
bronx 30
 
1.3%
science 28
 
1.2%
Other values (367) 1276
53.4%
2023-12-09T22:40:57.761970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1929
 
12.0%
o 1512
 
9.4%
e 1035
 
6.5%
h 956
 
6.0%
a 913
 
5.7%
i 905
 
5.7%
l 831
 
5.2%
n 831
 
5.2%
r 808
 
5.0%
c 764
 
4.8%
Other values (58) 5525
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11736
73.3%
Uppercase Letter 2184
 
13.6%
Space Separator 1929
 
12.0%
Other Punctuation 122
 
0.8%
Decimal Number 17
 
0.1%
Open Punctuation 7
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Close Punctuation 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1512
12.9%
e 1035
 
8.8%
h 956
 
8.1%
a 913
 
7.8%
i 905
 
7.7%
l 831
 
7.1%
n 831
 
7.1%
r 808
 
6.9%
c 764
 
6.5%
t 556
 
4.7%
Other values (16) 2625
22.4%
Uppercase Letter
ValueCountFrequency (%)
S 504
23.1%
H 371
17.0%
A 178
 
8.2%
C 171
 
7.8%
M 113
 
5.2%
B 113
 
5.2%
T 104
 
4.8%
L 83
 
3.8%
E 81
 
3.7%
P 70
 
3.2%
Other values (15) 396
18.1%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
3 4
23.5%
4 2
 
11.8%
7 2
 
11.8%
1 2
 
11.8%
6 1
 
5.9%
8 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 56
45.9%
, 37
30.3%
: 11
 
9.0%
& 8
 
6.6%
' 6
 
4.9%
/ 4
 
3.3%
Space Separator
ValueCountFrequency (%)
1929
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13920
87.0%
Common 2089
 
13.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1512
 
10.9%
e 1035
 
7.4%
h 956
 
6.9%
a 913
 
6.6%
i 905
 
6.5%
l 831
 
6.0%
n 831
 
6.0%
r 808
 
5.8%
c 764
 
5.5%
t 556
 
4.0%
Other values (41) 4809
34.5%
Common
ValueCountFrequency (%)
1929
92.3%
. 56
 
2.7%
, 37
 
1.8%
: 11
 
0.5%
& 8
 
0.4%
( 7
 
0.3%
- 7
 
0.3%
) 7
 
0.3%
' 6
 
0.3%
2 5
 
0.2%
Other values (7) 16
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1929
 
12.0%
o 1512
 
9.4%
e 1035
 
6.5%
h 956
 
6.0%
a 913
 
5.7%
i 905
 
5.7%
l 831
 
5.2%
n 831
 
5.2%
r 808
 
5.0%
c 764
 
4.8%
Other values (58) 5525
34.5%

tophs2
Text

MISSING 

Distinct192
Distinct (%)52.7%
Missing110
Missing (%)23.2%
Memory size36.1 KiB
2023-12-09T22:40:58.097193image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length78
Median length58
Mean length34.59340659
Min length16

Characters and Unicode

Total characters12592
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)31.3%

Sample

1st rowLower Manhattan Arts Academy
2nd rowBrooklyn Technical High School
3rd rowPace High School
4th rowStuyvesant High School
5th rowHigh School for Health Professions and Human Services
ValueCountFrequency (%)
school 322
 
16.8%
high 281
 
14.6%
and 75
 
3.9%
for 74
 
3.9%
academy 40
 
2.1%
the 40
 
2.1%
of 39
 
2.0%
arts 32
 
1.7%
technical 24
 
1.3%
brooklyn 22
 
1.1%
Other values (306) 970
50.5%
2023-12-09T22:40:58.623989image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1555
 
12.3%
o 1220
 
9.7%
h 850
 
6.8%
e 759
 
6.0%
i 747
 
5.9%
l 671
 
5.3%
a 657
 
5.2%
c 638
 
5.1%
r 610
 
4.8%
n 574
 
4.6%
Other values (55) 4311
34.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9164
72.8%
Uppercase Letter 1749
 
13.9%
Space Separator 1555
 
12.3%
Other Punctuation 92
 
0.7%
Decimal Number 9
 
0.1%
Close Punctuation 8
 
0.1%
Open Punctuation 8
 
0.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1220
13.3%
h 850
9.3%
e 759
 
8.3%
i 747
 
8.2%
l 671
 
7.3%
a 657
 
7.2%
c 638
 
7.0%
r 610
 
6.7%
n 574
 
6.3%
t 406
 
4.4%
Other values (16) 2032
22.2%
Uppercase Letter
ValueCountFrequency (%)
S 424
24.2%
H 348
19.9%
A 136
 
7.8%
C 126
 
7.2%
T 109
 
6.2%
M 79
 
4.5%
B 76
 
4.3%
E 59
 
3.4%
L 55
 
3.1%
P 55
 
3.1%
Other values (14) 282
16.1%
Decimal Number
ValueCountFrequency (%)
3 2
22.2%
6 2
22.2%
8 2
22.2%
1 1
11.1%
5 1
11.1%
7 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 60
65.2%
, 14
 
15.2%
& 10
 
10.9%
: 5
 
5.4%
/ 3
 
3.3%
Space Separator
ValueCountFrequency (%)
1555
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10913
86.7%
Common 1679
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1220
 
11.2%
h 850
 
7.8%
e 759
 
7.0%
i 747
 
6.8%
l 671
 
6.1%
a 657
 
6.0%
c 638
 
5.8%
r 610
 
5.6%
n 574
 
5.3%
S 424
 
3.9%
Other values (40) 3763
34.5%
Common
ValueCountFrequency (%)
1555
92.6%
. 60
 
3.6%
, 14
 
0.8%
& 10
 
0.6%
) 8
 
0.5%
( 8
 
0.5%
- 7
 
0.4%
: 5
 
0.3%
/ 3
 
0.2%
3 2
 
0.1%
Other values (5) 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12592
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1555
 
12.3%
o 1220
 
9.7%
h 850
 
6.8%
e 759
 
6.0%
i 747
 
5.9%
l 671
 
5.3%
a 657
 
5.2%
c 638
 
5.1%
r 610
 
4.8%
n 574
 
4.6%
Other values (55) 4311
34.2%

tophs3
Text

MISSING 

Distinct122
Distinct (%)59.5%
Missing269
Missing (%)56.8%
Memory size26.6 KiB
2023-12-09T22:40:58.999750image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length69
Median length54
Mean length33.35609756
Min length16

Characters and Unicode

Total characters6838
Distinct characters58
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)40.0%

Sample

1st rowThe Bronx High School of Science
2nd rowBrooklyn Technical High School
3rd rowStuyvesant High School
4th rowBrooklyn Technical High School
5th rowBrooklyn Technical High School
ValueCountFrequency (%)
school 186
 
17.6%
high 171
 
16.1%
for 37
 
3.5%
and 33
 
3.1%
the 26
 
2.5%
technical 23
 
2.2%
academy 22
 
2.1%
of 19
 
1.8%
bronx 15
 
1.4%
brooklyn 14
 
1.3%
Other values (210) 513
48.4%
2023-12-09T22:40:59.576415image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
854
 
12.5%
o 695
 
10.2%
h 482
 
7.0%
i 416
 
6.1%
e 389
 
5.7%
c 360
 
5.3%
l 360
 
5.3%
a 358
 
5.2%
n 343
 
5.0%
r 317
 
4.6%
Other values (48) 2264
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4956
72.5%
Uppercase Letter 975
 
14.3%
Space Separator 854
 
12.5%
Other Punctuation 49
 
0.7%
Dash Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 695
14.0%
h 482
9.7%
i 416
8.4%
e 389
 
7.8%
c 360
 
7.3%
l 360
 
7.3%
a 358
 
7.2%
n 343
 
6.9%
r 317
 
6.4%
g 227
 
4.6%
Other values (16) 1009
20.4%
Uppercase Letter
ValueCountFrequency (%)
S 233
23.9%
H 197
20.2%
T 67
 
6.9%
C 65
 
6.7%
B 64
 
6.6%
A 60
 
6.2%
E 43
 
4.4%
M 38
 
3.9%
F 27
 
2.8%
L 25
 
2.6%
Other values (14) 156
16.0%
Other Punctuation
ValueCountFrequency (%)
. 33
67.3%
, 8
 
16.3%
& 6
 
12.2%
: 2
 
4.1%
Space Separator
ValueCountFrequency (%)
854
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5931
86.7%
Common 907
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 695
 
11.7%
h 482
 
8.1%
i 416
 
7.0%
e 389
 
6.6%
c 360
 
6.1%
l 360
 
6.1%
a 358
 
6.0%
n 343
 
5.8%
r 317
 
5.3%
S 233
 
3.9%
Other values (40) 1978
33.4%
Common
ValueCountFrequency (%)
854
94.2%
. 33
 
3.6%
, 8
 
0.9%
& 6
 
0.7%
: 2
 
0.2%
- 2
 
0.2%
( 1
 
0.1%
) 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6838
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
854
 
12.5%
o 695
 
10.2%
h 482
 
7.0%
i 416
 
6.1%
e 389
 
5.7%
c 360
 
5.3%
l 360
 
5.3%
a 358
 
5.2%
n 343
 
5.0%
r 317
 
4.6%
Other values (48) 2264
33.1%

surveysafety
Text

MISSING 

Distinct42
Distinct (%)9.0%
Missing9
Missing (%)1.9%
Memory size27.2 KiB
2023-12-09T22:40:59.840463image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.002150538
Min length2

Characters and Unicode

Total characters931
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.9%

Sample

1st row74
2nd row76
3rd row81
4th row98
5th row85
ValueCountFrequency (%)
84 30
 
6.5%
88 28
 
6.0%
90 24
 
5.2%
82 24
 
5.2%
80 23
 
4.9%
83 22
 
4.7%
91 22
 
4.7%
85 22
 
4.7%
89 22
 
4.7%
79 19
 
4.1%
Other values (32) 229
49.2%
2023-12-09T22:41:00.214654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 263
28.2%
9 167
17.9%
7 147
15.8%
6 61
 
6.6%
4 56
 
6.0%
0 51
 
5.5%
3 48
 
5.2%
2 47
 
5.0%
1 47
 
5.0%
5 44
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 931
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 263
28.2%
9 167
17.9%
7 147
15.8%
6 61
 
6.6%
4 56
 
6.0%
0 51
 
5.5%
3 48
 
5.2%
2 47
 
5.0%
1 47
 
5.0%
5 44
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
Common 931
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 263
28.2%
9 167
17.9%
7 147
15.8%
6 61
 
6.6%
4 56
 
6.0%
0 51
 
5.5%
3 48
 
5.2%
2 47
 
5.0%
1 47
 
5.0%
5 44
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 931
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 263
28.2%
9 167
17.9%
7 147
15.8%
6 61
 
6.6%
4 56
 
6.0%
0 51
 
5.5%
3 48
 
5.2%
2 47
 
5.0%
1 47
 
5.0%
5 44
 
4.7%

totalstudents
Text

Distinct377
Distinct (%)80.0%
Missing3
Missing (%)0.6%
Memory size27.9 KiB
2023-12-09T22:41:00.707036image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.161358811
Min length2

Characters and Unicode

Total characters1489
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique299 ?
Unique (%)63.5%

Sample

1st row305
2nd row385
3rd row678
4th row407
5th row209
ValueCountFrequency (%)
230 4
 
0.8%
378 3
 
0.6%
312 3
 
0.6%
471 3
 
0.6%
678 3
 
0.6%
300 3
 
0.6%
362 3
 
0.6%
563 3
 
0.6%
407 3
 
0.6%
344 3
 
0.6%
Other values (367) 440
93.4%
2023-12-09T22:41:01.332999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 216
14.5%
3 171
11.5%
2 168
11.3%
5 166
11.1%
4 163
10.9%
6 144
9.7%
7 128
8.6%
0 118
7.9%
9 109
7.3%
8 106
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1489
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 216
14.5%
3 171
11.5%
2 168
11.3%
5 166
11.1%
4 163
10.9%
6 144
9.7%
7 128
8.6%
0 118
7.9%
9 109
7.3%
8 106
7.1%

Most occurring scripts

ValueCountFrequency (%)
Common 1489
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 216
14.5%
3 171
11.5%
2 168
11.3%
5 166
11.1%
4 163
10.9%
6 144
9.7%
7 128
8.6%
0 118
7.9%
9 109
7.3%
8 106
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 216
14.5%
3 171
11.5%
2 168
11.3%
5 166
11.1%
4 163
10.9%
6 144
9.7%
7 128
8.6%
0 118
7.9%
9 109
7.3%
8 106
7.1%

gradespan
Text

Distinct15
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size29.5 KiB
2023-12-09T22:41:01.505362image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.362869198
Min length4

Characters and Unicode

Total characters3016
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.3%

Sample

1st rowGr PK-8
2nd rowGr PK-8
3rd rowGr PK-8
4th rowGr PK-8
5th rowGr 6-8
ValueCountFrequency (%)
gr 474
50.0%
6-8 251
26.5%
pk-8 93
 
9.8%
6-12 74
 
7.8%
k-8 37
 
3.9%
6-7 4
 
0.4%
5-8 3
 
0.3%
6 2
 
0.2%
k-12 2
 
0.2%
pk-12 2
 
0.2%
Other values (6) 6
 
0.6%
2023-12-09T22:41:01.800176image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 474
15.7%
r 474
15.7%
474
15.7%
- 472
15.6%
8 386
12.8%
6 334
11.1%
K 134
 
4.4%
P 95
 
3.1%
1 82
 
2.7%
2 79
 
2.6%
Other values (6) 12
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 893
29.6%
Uppercase Letter 703
23.3%
Lowercase Letter 474
15.7%
Space Separator 474
15.7%
Dash Punctuation 472
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 386
43.2%
6 334
37.4%
1 82
 
9.2%
2 79
 
8.8%
7 5
 
0.6%
5 3
 
0.3%
4 1
 
0.1%
9 1
 
0.1%
3 1
 
0.1%
0 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
G 474
67.4%
K 134
 
19.1%
P 95
 
13.5%
Lowercase Letter
ValueCountFrequency (%)
r 474
100.0%
Space Separator
ValueCountFrequency (%)
474
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 472
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1839
61.0%
Latin 1177
39.0%

Most frequent character per script

Common
ValueCountFrequency (%)
474
25.8%
- 472
25.7%
8 386
21.0%
6 334
18.2%
1 82
 
4.5%
2 79
 
4.3%
7 5
 
0.3%
5 3
 
0.2%
4 1
 
0.1%
9 1
 
0.1%
Other values (2) 2
 
0.1%
Latin
ValueCountFrequency (%)
G 474
40.3%
r 474
40.3%
K 134
 
11.4%
P 95
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 474
15.7%
r 474
15.7%
474
15.7%
- 472
15.6%
8 386
12.8%
6 334
11.1%
K 134
 
4.4%
P 95
 
3.1%
1 82
 
2.7%
2 79
 
2.6%
Other values (6) 12
 
0.4%

diversityinadmissions
Text

MISSING 

Distinct6
Distinct (%)18.8%
Missing442
Missing (%)93.2%
Memory size20.6 KiB
2023-12-09T22:41:02.053635image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length345
Median length165
Mean length156.1875
Min length116

Characters and Unicode

Total characters4998
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)9.4%

Sample

1st rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 62 percent of the seats
2nd rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
3rd rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
4th rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 17 percent of seats
5th rowThis school will give priority to applicants eligible for Free and Reduced Lunch (FRL) for up to 60 percent of the seats
ValueCountFrequency (%)
for 53
 
6.7%
students 37
 
4.6%
of 34
 
4.3%
seats 34
 
4.3%
this 32
 
4.0%
and 31
 
3.9%
who 30
 
3.8%
program 30
 
3.8%
lunch 20
 
2.5%
free 20
 
2.5%
Other values (59) 475
59.7%
2023-12-09T22:41:02.428082image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
764
15.3%
e 390
 
7.8%
r 387
 
7.7%
o 369
 
7.4%
s 305
 
6.1%
i 261
 
5.2%
a 246
 
4.9%
t 227
 
4.5%
n 213
 
4.3%
h 175
 
3.5%
Other values (39) 1661
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3751
75.1%
Space Separator 764
 
15.3%
Uppercase Letter 203
 
4.1%
Decimal Number 100
 
2.0%
Other Punctuation 92
 
1.8%
Open Punctuation 31
 
0.6%
Close Punctuation 31
 
0.6%
Dash Punctuation 26
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 390
 
10.4%
r 387
 
10.3%
o 369
 
9.8%
s 305
 
8.1%
i 261
 
7.0%
a 246
 
6.6%
t 227
 
6.1%
n 213
 
5.7%
h 175
 
4.7%
f 160
 
4.3%
Other values (13) 1018
27.1%
Decimal Number
ValueCountFrequency (%)
5 34
34.0%
2 32
32.0%
1 11
 
11.0%
7 8
 
8.0%
6 4
 
4.0%
9 4
 
4.0%
3 3
 
3.0%
4 2
 
2.0%
0 1
 
1.0%
8 1
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
L 69
34.0%
F 25
 
12.3%
R 25
 
12.3%
S 24
 
11.8%
E 22
 
10.8%
T 21
 
10.3%
P 15
 
7.4%
D 2
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 33
35.9%
% 29
31.5%
. 28
30.4%
: 2
 
2.2%
Space Separator
ValueCountFrequency (%)
764
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3954
79.1%
Common 1044
 
20.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 390
 
9.9%
r 387
 
9.8%
o 369
 
9.3%
s 305
 
7.7%
i 261
 
6.6%
a 246
 
6.2%
t 227
 
5.7%
n 213
 
5.4%
h 175
 
4.4%
f 160
 
4.0%
Other values (21) 1221
30.9%
Common
ValueCountFrequency (%)
764
73.2%
5 34
 
3.3%
, 33
 
3.2%
2 32
 
3.1%
( 31
 
3.0%
) 31
 
3.0%
% 29
 
2.8%
. 28
 
2.7%
- 26
 
2.5%
1 11
 
1.1%
Other values (8) 25
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4998
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
764
15.3%
e 390
 
7.8%
r 387
 
7.7%
o 369
 
7.4%
s 305
 
6.1%
i 261
 
5.2%
a 246
 
4.9%
t 227
 
4.5%
n 213
 
4.3%
h 175
 
3.5%
Other values (39) 1661
33.2%

start_time
Text

MISSING 

Distinct33
Distinct (%)7.1%
Missing10
Missing (%)2.1%
Memory size29.0 KiB
2023-12-09T22:41:02.643427image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.961206897
Min length3

Characters and Unicode

Total characters2766
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.0%

Sample

1st row7:45am
2nd row8:00am
3rd row8:20am
4th row8:00am
5th row8:20am
ValueCountFrequency (%)
8:00am 190
40.7%
8:20am 70
 
15.0%
8:10am 54
 
11.6%
8:15am 32
 
6.9%
8:30am 24
 
5.1%
8:05am 14
 
3.0%
8:40am 13
 
2.8%
7:45am 12
 
2.6%
7:30am 6
 
1.3%
8:25am 5
 
1.1%
Other values (24) 47
 
10.1%
2023-12-09T22:41:02.981324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 579
20.9%
a 459
16.6%
m 459
16.6%
: 457
16.5%
8 426
15.4%
5 89
 
3.2%
1 87
 
3.1%
2 80
 
2.9%
3 40
 
1.4%
4 35
 
1.3%
Other values (8) 55
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1376
49.7%
Lowercase Letter 918
33.2%
Other Punctuation 457
 
16.5%
Uppercase Letter 12
 
0.4%
Space Separator 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 579
42.1%
8 426
31.0%
5 89
 
6.5%
1 87
 
6.3%
2 80
 
5.8%
3 40
 
2.9%
4 35
 
2.5%
7 33
 
2.4%
9 7
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
25.0%
M 3
25.0%
T 2
16.7%
B 2
16.7%
D 2
16.7%
Lowercase Letter
ValueCountFrequency (%)
a 459
50.0%
m 459
50.0%
Other Punctuation
ValueCountFrequency (%)
: 457
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1836
66.4%
Latin 930
33.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 579
31.5%
: 457
24.9%
8 426
23.2%
5 89
 
4.8%
1 87
 
4.7%
2 80
 
4.4%
3 40
 
2.2%
4 35
 
1.9%
7 33
 
1.8%
9 7
 
0.4%
Latin
ValueCountFrequency (%)
a 459
49.4%
m 459
49.4%
A 3
 
0.3%
M 3
 
0.3%
T 2
 
0.2%
B 2
 
0.2%
D 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2766
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 579
20.9%
a 459
16.6%
m 459
16.6%
: 457
16.5%
8 426
15.4%
5 89
 
3.2%
1 87
 
3.1%
2 80
 
2.9%
3 40
 
1.4%
4 35
 
1.3%
Other values (8) 55
 
2.0%

end_time
Text

MISSING 

Distinct63
Distinct (%)13.6%
Missing12
Missing (%)2.5%
Memory size28.9 KiB
2023-12-09T22:41:03.254097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length23
Median length6
Mean length5.88961039
Min length3

Characters and Unicode

Total characters2721
Distinct characters29
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)7.1%

Sample

1st row2:40pm
2nd row2:20pm
3rd row2:40pm
4th row2:50pm
5th row2:40pm
ValueCountFrequency (%)
2:20pm 153
32.5%
2:30pm 55
 
11.7%
2:40pm 51
 
10.8%
2:35pm 24
 
5.1%
2:50pm 22
 
4.7%
3:20pm 15
 
3.2%
3pm 12
 
2.5%
2:25pm 11
 
2.3%
4pm 10
 
2.1%
3:05pm 7
 
1.5%
Other values (56) 111
23.6%
2023-12-09T22:41:03.660040image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 562
20.7%
p 458
16.8%
m 458
16.8%
: 433
15.9%
0 339
12.5%
3 168
 
6.2%
5 120
 
4.4%
4 84
 
3.1%
1 32
 
1.2%
9
 
0.3%
Other values (19) 58
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1329
48.8%
Lowercase Letter 933
34.3%
Other Punctuation 433
 
15.9%
Uppercase Letter 13
 
0.5%
Space Separator 9
 
0.3%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 458
49.1%
m 458
49.1%
a 3
 
0.3%
s 3
 
0.3%
d 2
 
0.2%
y 2
 
0.2%
r 2
 
0.2%
i 2
 
0.2%
o 1
 
0.1%
n 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 562
42.3%
0 339
25.5%
3 168
 
12.6%
5 120
 
9.0%
4 84
 
6.3%
1 32
 
2.4%
6 9
 
0.7%
9 7
 
0.5%
8 4
 
0.3%
7 4
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
M 6
46.2%
P 5
38.5%
V 1
 
7.7%
F 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
: 433
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1775
65.2%
Latin 946
34.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
p 458
48.4%
m 458
48.4%
M 6
 
0.6%
P 5
 
0.5%
a 3
 
0.3%
s 3
 
0.3%
d 2
 
0.2%
y 2
 
0.2%
r 2
 
0.2%
i 2
 
0.2%
Other values (5) 5
 
0.5%
Common
ValueCountFrequency (%)
2 562
31.7%
: 433
24.4%
0 339
19.1%
3 168
 
9.5%
5 120
 
6.8%
4 84
 
4.7%
1 32
 
1.8%
9
 
0.5%
6 9
 
0.5%
9 7
 
0.4%
Other values (4) 12
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2721
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 562
20.7%
p 458
16.8%
m 458
16.8%
: 433
15.9%
0 339
12.5%
3 168
 
6.2%
5 120
 
4.4%
4 84
 
3.1%
1 32
 
1.2%
9
 
0.3%
Other values (19) 58
 
2.1%

ellprograms
Text

Distinct18
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size42.1 KiB
2023-12-09T22:41:03.881016image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length169
Median length25
Mean length33.6835443
Min length25

Characters and Unicode

Total characters15966
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)2.5%

Sample

1st rowEnglish as a New Language
2nd rowEnglish as a New Language
3rd rowEnglish as a New Language;Dual Language: Chinese
4th rowEnglish as a New Language;Dual Language: Spanish
5th rowEnglish as a New Language
ValueCountFrequency (%)
english 474
17.6%
as 474
17.6%
a 474
17.6%
new 474
17.6%
language 433
16.1%
spanish 87
 
3.2%
bilingual 62
 
2.3%
education 62
 
2.3%
language;dual 62
 
2.3%
language;transitional 44
 
1.6%
Other values (13) 43
 
1.6%
2023-12-09T22:41:04.236791image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2454
15.4%
2215
13.9%
g 1615
10.1%
n 1385
8.7%
s 1131
 
7.1%
e 1046
 
6.6%
i 913
 
5.7%
u 730
 
4.6%
l 729
 
4.6%
h 593
 
3.7%
Other values (23) 3155
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11629
72.8%
Space Separator 2215
 
13.9%
Uppercase Letter 1868
 
11.7%
Other Punctuation 254
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2454
21.1%
g 1615
13.9%
n 1385
11.9%
s 1131
9.7%
e 1046
9.0%
i 913
 
7.9%
u 730
 
6.3%
l 729
 
6.3%
h 593
 
5.1%
w 474
 
4.1%
Other values (7) 559
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
L 539
28.9%
E 536
28.7%
N 474
25.4%
S 104
 
5.6%
D 65
 
3.5%
B 63
 
3.4%
T 62
 
3.3%
C 15
 
0.8%
H 3
 
0.2%
F 2
 
0.1%
Other values (3) 5
 
0.3%
Other Punctuation
ValueCountFrequency (%)
: 127
50.0%
; 127
50.0%
Space Separator
ValueCountFrequency (%)
2215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13497
84.5%
Common 2469
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2454
18.2%
g 1615
12.0%
n 1385
10.3%
s 1131
8.4%
e 1046
7.7%
i 913
 
6.8%
u 730
 
5.4%
l 729
 
5.4%
h 593
 
4.4%
L 539
 
4.0%
Other values (20) 2362
17.5%
Common
ValueCountFrequency (%)
2215
89.7%
: 127
 
5.1%
; 127
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15966
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2454
15.4%
2215
13.9%
g 1615
10.1%
n 1385
8.7%
s 1131
 
7.1%
e 1046
 
6.6%
i 913
 
5.7%
u 730
 
4.6%
l 729
 
4.6%
h 593
 
3.7%
Other values (23) 3155
19.8%

other_features
Text

MISSING 

Distinct26
Distinct (%)8.3%
Missing162
Missing (%)34.2%
Memory size32.5 KiB
2023-12-09T22:41:04.469050image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length75
Median length59
Mean length32.63461538
Min length7

Characters and Unicode

Total characters10182
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.9%

Sample

1st rowExtended Day,Summer Session,Uniform,Weekend Program
2nd rowExtended Day,Summer Session,Uniform,Weekend Program
3rd rowExtended Day,Uniform
4th rowDiversity in Admissions,Extended Day,Summer Session,Weekend Program
5th rowUniform
ValueCountFrequency (%)
program 182
20.1%
extended 156
17.2%
day,summer 116
12.8%
session,uniform,weekend 112
12.4%
summer 66
 
7.3%
uniform 38
 
4.2%
session,uniform 37
 
4.1%
diversity 30
 
3.3%
in 30
 
3.3%
session,weekend 21
 
2.3%
Other values (12) 118
13.0%
2023-12-09T22:41:04.868753image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1280
12.6%
n 834
 
8.2%
m 818
 
8.0%
r 817
 
8.0%
o 635
 
6.2%
594
 
5.8%
i 573
 
5.6%
d 550
 
5.4%
, 492
 
4.8%
s 486
 
4.8%
Other values (16) 3103
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7728
75.9%
Uppercase Letter 1368
 
13.4%
Space Separator 594
 
5.8%
Other Punctuation 492
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1280
16.6%
n 834
10.8%
m 818
10.6%
r 817
10.6%
o 635
8.2%
i 573
7.4%
d 550
7.1%
s 486
 
6.3%
a 351
 
4.5%
f 240
 
3.1%
Other values (7) 1144
14.8%
Uppercase Letter
ValueCountFrequency (%)
S 366
26.8%
U 240
17.5%
D 199
14.5%
P 182
13.3%
W 182
13.3%
E 169
12.4%
A 30
 
2.2%
Space Separator
ValueCountFrequency (%)
594
100.0%
Other Punctuation
ValueCountFrequency (%)
, 492
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9096
89.3%
Common 1086
 
10.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1280
14.1%
n 834
 
9.2%
m 818
 
9.0%
r 817
 
9.0%
o 635
 
7.0%
i 573
 
6.3%
d 550
 
6.0%
s 486
 
5.3%
S 366
 
4.0%
a 351
 
3.9%
Other values (14) 2386
26.2%
Common
ValueCountFrequency (%)
594
54.7%
, 492
45.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10182
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1280
12.6%
n 834
 
8.2%
m 818
 
8.0%
r 817
 
8.0%
o 635
 
6.2%
594
 
5.8%
i 573
 
5.6%
d 550
 
5.4%
, 492
 
4.8%
s 486
 
4.8%
Other values (16) 3103
30.5%

languageclasses
Text

MISSING 

Distinct34
Distinct (%)9.5%
Missing115
Missing (%)24.3%
Memory size26.8 KiB
2023-12-09T22:41:05.107658image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length44
Median length7
Mean length8.919220056
Min length5

Characters and Unicode

Total characters3202
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)5.3%

Sample

1st rowSpanish
2nd rowSpanish
3rd rowCantonese;Mandarin
4th rowSpanish
5th rowMandarin
ValueCountFrequency (%)
spanish 268
70.2%
french 13
 
3.4%
french;spanish 11
 
2.9%
mandarin 10
 
2.6%
american 8
 
2.1%
sign 8
 
2.1%
italian;spanish 7
 
1.8%
language;spanish 7
 
1.8%
italian 6
 
1.6%
mandarin;spanish 6
 
1.6%
Other values (25) 38
 
9.9%
2023-12-09T22:41:05.495679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 470
14.7%
a 464
14.5%
i 387
12.1%
h 353
11.0%
S 323
10.1%
s 321
10.0%
p 316
9.9%
r 78
 
2.4%
e 76
 
2.4%
; 68
 
2.1%
Other values (22) 346
10.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2661
83.1%
Uppercase Letter 450
 
14.1%
Other Punctuation 68
 
2.1%
Space Separator 23
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 470
17.7%
a 464
17.4%
i 387
14.5%
h 353
13.3%
s 321
12.1%
p 316
11.9%
r 78
 
2.9%
e 76
 
2.9%
c 40
 
1.5%
g 38
 
1.4%
Other values (8) 118
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
S 323
71.8%
F 31
 
6.9%
M 25
 
5.6%
L 24
 
5.3%
I 19
 
4.2%
A 10
 
2.2%
O 7
 
1.6%
K 5
 
1.1%
C 3
 
0.7%
R 1
 
0.2%
Other values (2) 2
 
0.4%
Other Punctuation
ValueCountFrequency (%)
; 68
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3111
97.2%
Common 91
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 470
15.1%
a 464
14.9%
i 387
12.4%
h 353
11.3%
S 323
10.4%
s 321
10.3%
p 316
10.2%
r 78
 
2.5%
e 76
 
2.4%
c 40
 
1.3%
Other values (20) 283
9.1%
Common
ValueCountFrequency (%)
; 68
74.7%
23
 
25.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 470
14.7%
a 464
14.5%
i 387
12.1%
h 353
11.0%
S 323
10.1%
s 321
10.0%
p 316
9.9%
r 78
 
2.4%
e 76
 
2.4%
; 68
 
2.1%
Other values (22) 346
10.8%

acceleratedclasses
Text

MISSING 

Distinct51
Distinct (%)13.6%
Missing98
Missing (%)20.7%
Memory size34.8 KiB
2023-12-09T22:41:05.702282image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length100
Median length64
Mean length28.97340426
Min length6

Characters and Unicode

Total characters10894
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)7.2%

Sample

1st rowAlgebra I,Chinese,Living Environment
2nd rowAlgebra I
3rd rowAlgebra I,Geometry
4th rowAlgebra I,Chinese,Geometry,Living Environment,Spanish,US History
5th rowAlgebra I
ValueCountFrequency (%)
algebra 350
30.7%
i,living 184
16.1%
environment 142
12.5%
history 97
 
8.5%
i,earth 62
 
5.4%
i 52
 
4.6%
environment,us 50
 
4.4%
environment,spanish 27
 
2.4%
environment,spanish,us 25
 
2.2%
science 24
 
2.1%
Other values (37) 127
 
11.1%
2023-12-09T22:41:06.056374image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1167
 
10.7%
i 1021
 
9.4%
r 776
 
7.1%
764
 
7.0%
e 749
 
6.9%
g 622
 
5.7%
a 518
 
4.8%
, 518
 
4.8%
v 490
 
4.5%
t 426
 
3.9%
Other values (20) 3843
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7855
72.1%
Uppercase Letter 1757
 
16.1%
Space Separator 764
 
7.0%
Other Punctuation 518
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 1167
14.9%
i 1021
13.0%
r 776
9.9%
e 749
9.5%
g 622
7.9%
a 518
 
6.6%
v 490
 
6.2%
t 426
 
5.4%
l 393
 
5.0%
o 358
 
4.6%
Other values (7) 1335
17.0%
Uppercase Letter
ValueCountFrequency (%)
I 360
20.5%
A 352
20.0%
E 335
19.1%
L 246
14.0%
S 245
13.9%
H 102
 
5.8%
U 97
 
5.5%
G 11
 
0.6%
F 5
 
0.3%
C 3
 
0.2%
Space Separator
ValueCountFrequency (%)
764
100.0%
Other Punctuation
ValueCountFrequency (%)
, 518
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9612
88.2%
Common 1282
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 1167
 
12.1%
i 1021
 
10.6%
r 776
 
8.1%
e 749
 
7.8%
g 622
 
6.5%
a 518
 
5.4%
v 490
 
5.1%
t 426
 
4.4%
l 393
 
4.1%
I 360
 
3.7%
Other values (18) 3090
32.1%
Common
ValueCountFrequency (%)
764
59.6%
, 518
40.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 1167
 
10.7%
i 1021
 
9.4%
r 776
 
7.1%
764
 
7.0%
e 749
 
6.9%
g 622
 
5.7%
a 518
 
4.8%
, 518
 
4.8%
v 490
 
4.5%
t 426
 
3.9%
Other values (20) 3843
35.3%

electiveclasses
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing474
Missing (%)100.0%
Memory size3.8 KiB

activities
Text

MISSING 

Distinct347
Distinct (%)100.0%
Missing127
Missing (%)26.8%
Memory size94.7 KiB
2023-12-09T22:41:06.425244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length601
Median length276
Mean length210.3804035
Min length4

Characters and Unicode

Total characters73002
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique347 ?
Unique (%)100.0%

Sample

1st rowArt, Chorus, Dance, Homework Help, Music, National Junior Honor Society, Peer Mediation, Photography, Restorative Circles, School Newspaper, Student Council, Talent Show, Visual Arts, Yearbook
2nd rowArt, Dance, Leadership, Music, Restorative Circles, Saturday Academy, Spelling Bee, Technology, Tutoring, Visual Arts, Yearbook, Yoga
3rd rowSaturday Academy, Student Council, Technology, Yearbook
4th rowArt, Book Club, Chess, Gardening, Homework Help, Music, Peer Mediation, Restorative Circles, Student Council, Technology, Tutoring, Visual Arts, Yearbook, Yoga
5th rowArt, Band, Book Club, Chess, Coding, Comic Book Club, Cooking, Creative Writing, Dance, Debate, Drama, Fitness, Gardening, Green Team, Homework Help, Leadership, Math Team, Music, National Junior Honor Society, Peer Mediation, Photography, Robotics, Rock Band, Service Learning, STEM, Student Council, Talent Show, Technology, Tutoring, Video Game Club, Visual Arts, Yoga, Dungeons and Dragons Club, Gay-straight Alliance, Activism Club, Brotherhood, Sisterhood
ValueCountFrequency (%)
club 334
 
3.6%
art 278
 
3.0%
team 269
 
2.9%
student 259
 
2.8%
council 245
 
2.6%
theater 245
 
2.6%
yearbook 231
 
2.5%
robotics 228
 
2.4%
dance 212
 
2.3%
arts 211
 
2.2%
Other values (434) 6887
73.3%
2023-12-09T22:41:08.334616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9055
 
12.4%
e 6316
 
8.7%
, 5689
 
7.8%
o 4863
 
6.7%
a 4281
 
5.9%
i 3855
 
5.3%
r 3759
 
5.1%
t 3639
 
5.0%
n 3360
 
4.6%
s 2383
 
3.3%
Other values (58) 25802
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 48308
66.2%
Uppercase Letter 9859
 
13.5%
Space Separator 9055
 
12.4%
Other Punctuation 5719
 
7.8%
Dash Punctuation 23
 
< 0.1%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Decimal Number 10
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 6316
13.1%
o 4863
10.1%
a 4281
 
8.9%
i 3855
 
8.0%
r 3759
 
7.8%
t 3639
 
7.5%
n 3360
 
7.0%
s 2383
 
4.9%
l 2192
 
4.5%
c 2162
 
4.5%
Other values (16) 11498
23.8%
Uppercase Letter
ValueCountFrequency (%)
C 1472
14.9%
S 1370
13.9%
T 1129
11.5%
A 736
 
7.5%
M 702
 
7.1%
D 532
 
5.4%
H 512
 
5.2%
B 482
 
4.9%
R 435
 
4.4%
L 384
 
3.9%
Other values (15) 2105
21.4%
Other Punctuation
ValueCountFrequency (%)
, 5689
99.5%
/ 7
 
0.1%
. 7
 
0.1%
: 6
 
0.1%
& 4
 
0.1%
" 4
 
0.1%
' 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
4 2
20.0%
0 2
20.0%
2 2
20.0%
5 2
20.0%
3 1
10.0%
8 1
10.0%
Space Separator
ValueCountFrequency (%)
9055
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 58167
79.7%
Common 14835
 
20.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 6316
 
10.9%
o 4863
 
8.4%
a 4281
 
7.4%
i 3855
 
6.6%
r 3759
 
6.5%
t 3639
 
6.3%
n 3360
 
5.8%
s 2383
 
4.1%
l 2192
 
3.8%
c 2162
 
3.7%
Other values (41) 21357
36.7%
Common
ValueCountFrequency (%)
9055
61.0%
, 5689
38.3%
- 23
 
0.2%
( 14
 
0.1%
) 14
 
0.1%
/ 7
 
< 0.1%
. 7
 
< 0.1%
: 6
 
< 0.1%
& 4
 
< 0.1%
" 4
 
< 0.1%
Other values (7) 12
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73002
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9055
 
12.4%
e 6316
 
8.7%
, 5689
 
7.8%
o 4863
 
6.7%
a 4281
 
5.9%
i 3855
 
5.3%
r 3759
 
5.1%
t 3639
 
5.0%
n 3360
 
4.6%
s 2383
 
3.3%
Other values (58) 25802
35.3%

champsboys
Text

MISSING 

Distinct9
Distinct (%)27.3%
Missing441
Missing (%)93.0%
Memory size16.1 KiB
2023-12-09T22:41:08.529992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length22
Median length15
Mean length10.33333333
Min length5

Characters and Unicode

Total characters341
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)15.2%

Sample

1st rowBaseball,Soccer
2nd rowBaseball
3rd rowBaseball
4th rowFlag Football
5th rowFlag Football
ValueCountFrequency (%)
football 12
26.1%
flag 11
23.9%
baseball 9
19.6%
soccer 6
13.0%
softball 2
 
4.3%
baseball,cross 1
 
2.2%
country 1
 
2.2%
dance 1
 
2.2%
baseball,flag 1
 
2.2%
baseball,soccer 1
 
2.2%
2023-12-09T22:41:08.841537image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 68
19.9%
a 52
15.2%
o 36
10.6%
b 27
 
7.9%
F 24
 
7.0%
e 21
 
6.2%
t 15
 
4.4%
c 15
 
4.4%
s 14
 
4.1%
13
 
3.8%
Other values (12) 56
16.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 276
80.9%
Uppercase Letter 49
 
14.4%
Space Separator 13
 
3.8%
Other Punctuation 3
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 68
24.6%
a 52
18.8%
o 36
13.0%
b 27
 
9.8%
e 21
 
7.6%
t 15
 
5.4%
c 15
 
5.4%
s 14
 
5.1%
g 12
 
4.3%
r 9
 
3.3%
Other values (4) 7
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
F 24
49.0%
B 12
24.5%
S 9
 
18.4%
C 2
 
4.1%
D 1
 
2.0%
V 1
 
2.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 325
95.3%
Common 16
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 68
20.9%
a 52
16.0%
o 36
11.1%
b 27
 
8.3%
F 24
 
7.4%
e 21
 
6.5%
t 15
 
4.6%
c 15
 
4.6%
s 14
 
4.3%
g 12
 
3.7%
Other values (10) 41
12.6%
Common
ValueCountFrequency (%)
13
81.2%
, 3
 
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 341
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 68
19.9%
a 52
15.2%
o 36
10.6%
b 27
 
7.9%
F 24
 
7.0%
e 21
 
6.2%
t 15
 
4.4%
c 15
 
4.4%
s 14
 
4.1%
13
 
3.8%
Other values (12) 56
16.4%

champsgirls
Text

MISSING 

Distinct10
Distinct (%)20.8%
Missing426
Missing (%)89.9%
Memory size16.6 KiB
2023-12-09T22:41:09.032097image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length19
Median length10
Mean length10.3125
Min length5

Characters and Unicode

Total characters495
Distinct characters24
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)14.6%

Sample

1st rowCheerleading
2nd rowVolleyball
3rd rowSoftball
4th rowSoftball
5th rowSoftball
ValueCountFrequency (%)
volleyball 26
51.0%
softball 13
25.5%
softball,volleyball 2
 
3.9%
soccer,table 1
 
2.0%
tennis 1
 
2.0%
tennis,volleyball 1
 
2.0%
cross 1
 
2.0%
country 1
 
2.0%
soccer,softball 1
 
2.0%
dance 1
 
2.0%
Other values (3) 3
 
5.9%
2023-12-09T22:41:09.350602image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 151
30.5%
o 50
 
10.1%
a 48
 
9.7%
b 47
 
9.5%
e 39
 
7.9%
y 30
 
6.1%
V 29
 
5.9%
S 18
 
3.6%
t 18
 
3.6%
f 16
 
3.2%
Other values (14) 49
 
9.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 431
87.1%
Uppercase Letter 56
 
11.3%
Other Punctuation 5
 
1.0%
Space Separator 3
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 151
35.0%
o 50
 
11.6%
a 48
 
11.1%
b 47
 
10.9%
e 39
 
9.0%
y 30
 
7.0%
t 18
 
4.2%
f 16
 
3.7%
n 7
 
1.6%
c 6
 
1.4%
Other values (7) 19
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
V 29
51.8%
S 18
32.1%
T 3
 
5.4%
C 3
 
5.4%
D 3
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 487
98.4%
Common 8
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 151
31.0%
o 50
 
10.3%
a 48
 
9.9%
b 47
 
9.7%
e 39
 
8.0%
y 30
 
6.2%
V 29
 
6.0%
S 18
 
3.7%
t 18
 
3.7%
f 16
 
3.3%
Other values (12) 41
 
8.4%
Common
ValueCountFrequency (%)
, 5
62.5%
3
37.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 495
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 151
30.5%
o 50
 
10.1%
a 48
 
9.7%
b 47
 
9.5%
e 39
 
7.9%
y 30
 
6.1%
V 29
 
5.9%
S 18
 
3.6%
t 18
 
3.6%
f 16
 
3.2%
Other values (14) 49
 
9.9%

champscoed
Text

MISSING 

Distinct53
Distinct (%)23.3%
Missing247
Missing (%)52.1%
Memory size23.7 KiB
2023-12-09T22:41:09.573834image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length40
Median length35
Mean length14.33039648
Min length5

Characters and Unicode

Total characters3253
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)13.7%

Sample

1st rowFlag Football
2nd rowCross Country
3rd rowBadminton
4th rowFlag Football,Softball
5th rowBaseball,Dance,Flag Football,Soccer
ValueCountFrequency (%)
flag 65
19.2%
football 57
16.8%
soccer 37
10.9%
volleyball 23
 
6.8%
cross 21
 
6.2%
soccer,volleyball 18
 
5.3%
country 13
 
3.8%
dance 10
 
2.9%
football,volleyball 10
 
2.9%
football,soccer 10
 
2.9%
Other values (44) 75
22.1%
2023-12-09T22:41:09.953055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 566
17.4%
o 382
11.7%
a 315
 
9.7%
e 220
 
6.8%
c 191
 
5.9%
b 178
 
5.5%
F 164
 
5.0%
r 136
 
4.2%
t 132
 
4.1%
112
 
3.4%
Other values (21) 857
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2592
79.7%
Uppercase Letter 444
 
13.6%
Space Separator 112
 
3.4%
Other Punctuation 105
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 566
21.8%
o 382
14.7%
a 315
12.2%
e 220
 
8.5%
c 191
 
7.4%
b 178
 
6.9%
r 136
 
5.2%
t 132
 
5.1%
n 98
 
3.8%
g 90
 
3.5%
Other values (10) 284
11.0%
Uppercase Letter
ValueCountFrequency (%)
F 164
36.9%
S 93
20.9%
V 65
 
14.6%
C 52
 
11.7%
B 30
 
6.8%
D 23
 
5.2%
T 15
 
3.4%
G 1
 
0.2%
L 1
 
0.2%
Space Separator
ValueCountFrequency (%)
112
100.0%
Other Punctuation
ValueCountFrequency (%)
, 105
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3036
93.3%
Common 217
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 566
18.6%
o 382
12.6%
a 315
10.4%
e 220
 
7.2%
c 191
 
6.3%
b 178
 
5.9%
F 164
 
5.4%
r 136
 
4.5%
t 132
 
4.3%
n 98
 
3.2%
Other values (19) 654
21.5%
Common
ValueCountFrequency (%)
112
51.6%
, 105
48.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3253
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 566
17.4%
o 382
11.7%
a 315
 
9.7%
e 220
 
6.8%
c 191
 
5.9%
b 178
 
5.5%
F 164
 
5.0%
r 136
 
4.2%
t 132
 
4.1%
112
 
3.4%
Other values (21) 857
26.3%

othersports
Text

MISSING 

Distinct277
Distinct (%)80.1%
Missing128
Missing (%)27.0%
Memory size42.0 KiB
2023-12-09T22:41:10.198612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length244
Median length125
Mean length55.03179191
Min length4

Characters and Unicode

Total characters19041
Distinct characters51
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)72.3%

Sample

1st rowBasketball, Fitness Club, Flag Football
2nd rowSports are only by champs
3rd rowRunning Club, Volleyball
4th rowBadminton, Basketball, Flag Football
5th rowFitness Club, Flag Football, Running Club, Soccer, Softball, Yoga
ValueCountFrequency (%)
basketball 267
 
11.4%
club 153
 
6.6%
soccer 151
 
6.5%
volleyball 131
 
5.6%
dance 130
 
5.6%
football 129
 
5.5%
flag 115
 
4.9%
and 105
 
4.5%
field 103
 
4.4%
track 102
 
4.4%
Other values (95) 949
40.6%
2023-12-09T22:41:10.619183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 2225
 
11.7%
1990
 
10.5%
a 1774
 
9.3%
e 1502
 
7.9%
, 1341
 
7.0%
n 942
 
4.9%
b 906
 
4.8%
o 806
 
4.2%
t 765
 
4.0%
s 751
 
3.9%
Other values (41) 6039
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13496
70.9%
Uppercase Letter 2208
 
11.6%
Space Separator 1990
 
10.5%
Other Punctuation 1344
 
7.1%
Dash Punctuation 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 2225
16.5%
a 1774
13.1%
e 1502
11.1%
n 942
 
7.0%
b 906
 
6.7%
o 806
 
6.0%
t 765
 
5.7%
s 751
 
5.6%
c 616
 
4.6%
i 592
 
4.4%
Other values (13) 2617
19.4%
Uppercase Letter
ValueCountFrequency (%)
F 444
20.1%
B 383
17.3%
C 326
14.8%
S 275
12.5%
T 184
8.3%
D 157
 
7.1%
V 136
 
6.2%
R 91
 
4.1%
Y 40
 
1.8%
A 37
 
1.7%
Other values (13) 135
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 1341
99.8%
/ 2
 
0.1%
. 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15704
82.5%
Common 3337
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 2225
14.2%
a 1774
 
11.3%
e 1502
 
9.6%
n 942
 
6.0%
b 906
 
5.8%
o 806
 
5.1%
t 765
 
4.9%
s 751
 
4.8%
c 616
 
3.9%
i 592
 
3.8%
Other values (36) 4825
30.7%
Common
ValueCountFrequency (%)
1990
59.6%
, 1341
40.2%
- 3
 
0.1%
/ 2
 
0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19041
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 2225
 
11.7%
1990
 
10.5%
a 1774
 
9.3%
e 1502
 
7.9%
, 1341
 
7.0%
n 942
 
4.9%
b 906
 
4.8%
o 806
 
4.2%
t 765
 
4.0%
s 751
 
3.9%
Other values (41) 6039
31.7%

postcode
Text

Distinct150
Distinct (%)31.7%
Missing1
Missing (%)0.2%
Memory size28.8 KiB
2023-12-09T22:41:11.049092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2365
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)8.9%

Sample

1st row10009
2nd row10002
3rd row10002
4th row10002
5th row10002
ValueCountFrequency (%)
10457 14
 
3.0%
10456 14
 
3.0%
11212 10
 
2.1%
10029 10
 
2.1%
10453 10
 
2.1%
11204 9
 
1.9%
11207 9
 
1.9%
10027 9
 
1.9%
10467 9
 
1.9%
10460 8
 
1.7%
Other values (140) 371
78.4%
2023-12-09T22:41:11.599625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 834
35.3%
0 432
18.3%
2 278
 
11.8%
4 215
 
9.1%
3 192
 
8.1%
5 123
 
5.2%
6 117
 
4.9%
7 81
 
3.4%
9 52
 
2.2%
8 41
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2365
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 834
35.3%
0 432
18.3%
2 278
 
11.8%
4 215
 
9.1%
3 192
 
8.1%
5 123
 
5.2%
6 117
 
4.9%
7 81
 
3.4%
9 52
 
2.2%
8 41
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Common 2365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 834
35.3%
0 432
18.3%
2 278
 
11.8%
4 215
 
9.1%
3 192
 
8.1%
5 123
 
5.2%
6 117
 
4.9%
7 81
 
3.4%
9 52
 
2.2%
8 41
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 834
35.3%
0 432
18.3%
2 278
 
11.8%
4 215
 
9.1%
3 192
 
8.1%
5 123
 
5.2%
6 117
 
4.9%
7 81
 
3.4%
9 52
 
2.2%
8 41
 
1.7%

borough
Text

Distinct5
Distinct (%)1.1%
Missing1
Missing (%)0.2%
Memory size29.7 KiB
2023-12-09T22:41:11.785992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.050739958
Min length5

Characters and Unicode

Total characters3335
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMANHATTAN
2nd rowMANHATTAN
3rd rowMANHATTAN
4th rowMANHATTAN
5th rowMANHATTAN
ValueCountFrequency (%)
brooklyn 143
29.3%
bronx 116
23.8%
queens 105
21.5%
manhattan 94
19.3%
staten 15
 
3.1%
is 15
 
3.1%
2023-12-09T22:41:12.091326image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 567
17.0%
O 402
12.1%
A 297
8.9%
B 259
 
7.8%
R 259
 
7.8%
E 225
 
6.7%
T 218
 
6.5%
K 143
 
4.3%
L 143
 
4.3%
Y 143
 
4.3%
Other values (8) 679
20.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3320
99.6%
Space Separator 15
 
0.4%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 567
17.1%
O 402
12.1%
A 297
8.9%
B 259
 
7.8%
R 259
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 143
 
4.3%
L 143
 
4.3%
Y 143
 
4.3%
Other values (7) 664
20.0%
Space Separator
ValueCountFrequency (%)
15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3320
99.6%
Common 15
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 567
17.1%
O 402
12.1%
A 297
8.9%
B 259
 
7.8%
R 259
 
7.8%
E 225
 
6.8%
T 218
 
6.6%
K 143
 
4.3%
L 143
 
4.3%
Y 143
 
4.3%
Other values (7) 664
20.0%
Common
ValueCountFrequency (%)
15
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3335
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 567
17.0%
O 402
12.1%
A 297
8.9%
B 259
 
7.8%
R 259
 
7.8%
E 225
 
6.7%
T 218
 
6.5%
K 143
 
4.3%
L 143
 
4.3%
Y 143
 
4.3%
Other values (8) 679
20.4%

latitude
Text

Distinct413
Distinct (%)87.3%
Missing1
Missing (%)0.2%
Memory size30.6 KiB
2023-12-09T22:41:12.450438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.862579281
Min length7

Characters and Unicode

Total characters4192
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)75.9%

Sample

1st row40.726473
2nd row40.71925
3rd row40.711549
4th row40.719598
5th row40.713684
ValueCountFrequency (%)
40.791709 3
 
0.6%
40.884953 3
 
0.6%
40.69719 3
 
0.6%
40.827941 3
 
0.6%
40.780822 3
 
0.6%
40.862109 3
 
0.6%
40.649787 2
 
0.4%
40.623561 2
 
0.4%
40.81004 2
 
0.4%
40.675771 2
 
0.4%
Other values (403) 447
94.5%
2023-12-09T22:41:12.951478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 716
17.1%
0 667
15.9%
. 473
11.3%
8 390
9.3%
6 385
9.2%
7 378
9.0%
5 287
6.8%
3 236
 
5.6%
2 225
 
5.4%
9 222
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3719
88.7%
Other Punctuation 473
 
11.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 716
19.3%
0 667
17.9%
8 390
10.5%
6 385
10.4%
7 378
10.2%
5 287
7.7%
3 236
 
6.3%
2 225
 
6.1%
9 222
 
6.0%
1 213
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 473
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4192
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 716
17.1%
0 667
15.9%
. 473
11.3%
8 390
9.3%
6 385
9.2%
7 378
9.0%
5 287
6.8%
3 236
 
5.6%
2 225
 
5.4%
9 222
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4192
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 716
17.1%
0 667
15.9%
. 473
11.3%
8 390
9.3%
6 385
9.2%
7 378
9.0%
5 287
6.8%
3 236
 
5.6%
2 225
 
5.4%
9 222
 
5.3%

longitude
Text

Distinct413
Distinct (%)87.3%
Missing1
Missing (%)0.2%
Memory size31.1 KiB
2023-12-09T22:41:13.334074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.885835095
Min length7

Characters and Unicode

Total characters4676
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique359 ?
Unique (%)75.9%

Sample

1st row-73.975181
2nd row-73.983056
3rd row-73.986542
4th row-73.977904
5th row-73.986336
ValueCountFrequency (%)
73.864577 3
 
0.6%
73.787192 3
 
0.6%
73.970802 3
 
0.6%
73.840524 3
 
0.6%
73.976855 3
 
0.6%
73.914374 3
 
0.6%
73.905927 2
 
0.4%
73.921631 2
 
0.4%
73.749097 2
 
0.4%
74.006862 2
 
0.4%
Other values (403) 447
94.5%
2023-12-09T22:41:13.837054image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 780
16.7%
3 659
14.1%
9 487
10.4%
- 473
10.1%
. 473
10.1%
8 366
7.8%
1 263
 
5.6%
4 262
 
5.6%
5 234
 
5.0%
2 234
 
5.0%
Other values (2) 445
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3730
79.8%
Dash Punctuation 473
 
10.1%
Other Punctuation 473
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 780
20.9%
3 659
17.7%
9 487
13.1%
8 366
9.8%
1 263
 
7.1%
4 262
 
7.0%
5 234
 
6.3%
2 234
 
6.3%
0 223
 
6.0%
6 222
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 473
100.0%
Other Punctuation
ValueCountFrequency (%)
. 473
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 780
16.7%
3 659
14.1%
9 487
10.4%
- 473
10.1%
. 473
10.1%
8 366
7.8%
1 263
 
5.6%
4 262
 
5.6%
5 234
 
5.0%
2 234
 
5.0%
Other values (2) 445
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 780
16.7%
3 659
14.1%
9 487
10.4%
- 473
10.1%
. 473
10.1%
8 366
7.8%
1 263
 
5.6%
4 262
 
5.6%
5 234
 
5.0%
2 234
 
5.0%
Other values (2) 445
9.5%

community_board
Text

Distinct59
Distinct (%)12.5%
Missing1
Missing (%)0.2%
Memory size27.9 KiB
2023-12-09T22:41:14.138014image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1419
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.4%

Sample

1st row103
2nd row103
3rd row103
4th row103
5th row103
ValueCountFrequency (%)
305 17
 
3.6%
112 16
 
3.4%
204 15
 
3.2%
107 14
 
3.0%
316 14
 
3.0%
412 14
 
3.0%
111 14
 
3.0%
414 14
 
3.0%
206 14
 
3.0%
203 13
 
2.7%
Other values (49) 328
69.3%
2023-12-09T22:41:14.542514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 352
24.8%
0 320
22.6%
3 199
14.0%
2 187
13.2%
4 155
10.9%
5 62
 
4.4%
7 44
 
3.1%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1419
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 352
24.8%
0 320
22.6%
3 199
14.0%
2 187
13.2%
4 155
10.9%
5 62
 
4.4%
7 44
 
3.1%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
Common 1419
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 352
24.8%
0 320
22.6%
3 199
14.0%
2 187
13.2%
4 155
10.9%
5 62
 
4.4%
7 44
 
3.1%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 352
24.8%
0 320
22.6%
3 199
14.0%
2 187
13.2%
4 155
10.9%
5 62
 
4.4%
7 44
 
3.1%
6 40
 
2.8%
8 35
 
2.5%
9 25
 
1.8%

council_district
Text

Distinct51
Distinct (%)10.8%
Missing1
Missing (%)0.2%
Memory size27.3 KiB
2023-12-09T22:41:14.807406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.820295983
Min length1

Characters and Unicode

Total characters861
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2
2nd row1
3rd row1
4th row2
5th row1
ValueCountFrequency (%)
16 21
 
4.4%
8 20
 
4.2%
17 20
 
4.2%
37 16
 
3.4%
31 15
 
3.2%
10 15
 
3.2%
42 15
 
3.2%
14 14
 
3.0%
15 13
 
2.7%
13 13
 
2.7%
Other values (41) 311
65.8%
2023-12-09T22:41:15.185916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 190
22.1%
3 141
16.4%
4 128
14.9%
2 116
13.5%
7 65
 
7.5%
6 55
 
6.4%
8 51
 
5.9%
5 46
 
5.3%
0 36
 
4.2%
9 33
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 861
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 190
22.1%
3 141
16.4%
4 128
14.9%
2 116
13.5%
7 65
 
7.5%
6 55
 
6.4%
8 51
 
5.9%
5 46
 
5.3%
0 36
 
4.2%
9 33
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Common 861
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 190
22.1%
3 141
16.4%
4 128
14.9%
2 116
13.5%
7 65
 
7.5%
6 55
 
6.4%
8 51
 
5.9%
5 46
 
5.3%
0 36
 
4.2%
9 33
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 861
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 190
22.1%
3 141
16.4%
4 128
14.9%
2 116
13.5%
7 65
 
7.5%
6 55
 
6.4%
8 51
 
5.9%
5 46
 
5.3%
0 36
 
4.2%
9 33
 
3.8%

census_tract
Text

Distinct341
Distinct (%)72.1%
Missing1
Missing (%)0.2%
Memory size28.0 KiB
2023-12-09T22:41:15.679101image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.268498943
Min length1

Characters and Unicode

Total characters1546
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique240 ?
Unique (%)50.7%

Sample

1st row28
2nd row2201
3rd row201
4th row20
5th row201
ValueCountFrequency (%)
330 5
 
1.1%
69 4
 
0.8%
177 4
 
0.8%
73 4
 
0.8%
291 4
 
0.8%
161 4
 
0.8%
77 3
 
0.6%
409 3
 
0.6%
285 3
 
0.6%
484 3
 
0.6%
Other values (331) 436
92.2%
2023-12-09T22:41:16.294514image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 260
16.8%
2 218
14.1%
0 178
11.5%
3 176
11.4%
4 150
9.7%
9 121
7.8%
7 118
7.6%
8 111
7.2%
5 110
7.1%
6 104
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1546
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 260
16.8%
2 218
14.1%
0 178
11.5%
3 176
11.4%
4 150
9.7%
9 121
7.8%
7 118
7.6%
8 111
7.2%
5 110
7.1%
6 104
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Common 1546
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 260
16.8%
2 218
14.1%
0 178
11.5%
3 176
11.4%
4 150
9.7%
9 121
7.8%
7 118
7.6%
8 111
7.2%
5 110
7.1%
6 104
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1546
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 260
16.8%
2 218
14.1%
0 178
11.5%
3 176
11.4%
4 150
9.7%
9 121
7.8%
7 118
7.6%
8 111
7.2%
5 110
7.1%
6 104
 
6.7%

bin
Text

Distinct411
Distinct (%)87.1%
Missing2
Missing (%)0.4%
Memory size29.7 KiB
2023-12-09T22:41:16.719827image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters3304
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique356 ?
Unique (%)75.4%

Sample

1st row1004564
2nd row1004091
3rd row1003143
4th row1004349
5th row1003223
ValueCountFrequency (%)
1032522 3
 
0.6%
4216655 3
 
0.6%
2051313 3
 
0.6%
1030178 3
 
0.6%
2066190 3
 
0.6%
2097111 3
 
0.6%
4234318 2
 
0.4%
3336215 2
 
0.4%
2002410 2
 
0.4%
2002458 2
 
0.4%
Other values (401) 446
94.5%
2023-12-09T22:41:17.260207image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 580
17.6%
1 423
12.8%
3 411
12.4%
4 382
11.6%
2 362
11.0%
8 245
7.4%
5 239
7.2%
6 224
 
6.8%
7 223
 
6.7%
9 215
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3304
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 580
17.6%
1 423
12.8%
3 411
12.4%
4 382
11.6%
2 362
11.0%
8 245
7.4%
5 239
7.2%
6 224
 
6.8%
7 223
 
6.7%
9 215
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
Common 3304
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 580
17.6%
1 423
12.8%
3 411
12.4%
4 382
11.6%
2 362
11.0%
8 245
7.4%
5 239
7.2%
6 224
 
6.8%
7 223
 
6.7%
9 215
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3304
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 580
17.6%
1 423
12.8%
3 411
12.4%
4 382
11.6%
2 362
11.0%
8 245
7.4%
5 239
7.2%
6 224
 
6.8%
7 223
 
6.7%
9 215
 
6.5%

bbl
Text

Distinct407
Distinct (%)86.2%
Missing2
Missing (%)0.4%
Memory size31.1 KiB
2023-12-09T22:41:17.584149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters4720
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique348 ?
Unique (%)73.7%

Sample

1st row1003810038
2nd row1003440001
3rd row1002450007
4th row1003560100
5th row1002690041
ValueCountFrequency (%)
2049350001 3
 
0.6%
2024240001 3
 
0.6%
4101780001 3
 
0.6%
2044320001 3
 
0.6%
1012230005 3
 
0.6%
1011480014 3
 
0.6%
2022860036 2
 
0.4%
3016160001 2
 
0.4%
2046750020 2
 
0.4%
2029250001 2
 
0.4%
Other values (397) 446
94.5%
2023-12-09T22:41:18.009660image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1822
38.6%
1 685
 
14.5%
3 447
 
9.5%
2 446
 
9.4%
4 369
 
7.8%
5 240
 
5.1%
6 208
 
4.4%
8 186
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4720
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1822
38.6%
1 685
 
14.5%
3 447
 
9.5%
2 446
 
9.4%
4 369
 
7.8%
5 240
 
5.1%
6 208
 
4.4%
8 186
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
Common 4720
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1822
38.6%
1 685
 
14.5%
3 447
 
9.5%
2 446
 
9.4%
4 369
 
7.8%
5 240
 
5.1%
6 208
 
4.4%
8 186
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1822
38.6%
1 685
 
14.5%
3 447
 
9.5%
2 446
 
9.4%
4 369
 
7.8%
5 240
 
5.1%
6 208
 
4.4%
8 186
 
3.9%
7 165
 
3.5%
9 152
 
3.2%

nta
Text

Distinct164
Distinct (%)34.7%
Missing1
Missing (%)0.2%
Memory size35.6 KiB
2023-12-09T22:41:18.305668image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Length

Max length56
Median length39
Mean length19.74207188
Min length6

Characters and Unicode

Total characters9338
Distinct characters55
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)9.7%

Sample

1st rowLower East Side
2nd rowLower East Side
3rd rowLower East Side
4th rowLower East Side
5th rowLower East Side
ValueCountFrequency (%)
east 70
 
6.4%
heights 43
 
3.9%
park 39
 
3.6%
south 37
 
3.4%
north 36
 
3.3%
village 26
 
2.4%
harlem 23
 
2.1%
west 22
 
2.0%
side 19
 
1.7%
hill 17
 
1.6%
Other values (224) 758
69.5%
2023-12-09T22:41:18.756966image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 805
 
8.6%
a 675
 
7.2%
o 622
 
6.7%
r 621
 
6.7%
617
 
6.6%
t 614
 
6.6%
n 533
 
5.7%
s 505
 
5.4%
l 479
 
5.1%
i 459
 
4.9%
Other values (45) 3408
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7076
75.8%
Uppercase Letter 1367
 
14.6%
Space Separator 617
 
6.6%
Dash Punctuation 263
 
2.8%
Other Punctuation 7
 
0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 805
11.4%
a 675
9.5%
o 622
8.8%
r 621
8.8%
t 614
8.7%
n 533
 
7.5%
s 505
 
7.1%
l 479
 
6.8%
i 459
 
6.5%
h 291
 
4.1%
Other values (15) 1472
20.8%
Uppercase Letter
ValueCountFrequency (%)
H 190
13.9%
B 140
10.2%
S 131
9.6%
C 125
 
9.1%
P 100
 
7.3%
E 95
 
6.9%
M 88
 
6.4%
N 67
 
4.9%
W 56
 
4.1%
G 49
 
3.6%
Other values (14) 326
23.8%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
' 2
 
28.6%
Space Separator
ValueCountFrequency (%)
617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 263
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8443
90.4%
Common 895
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 805
 
9.5%
a 675
 
8.0%
o 622
 
7.4%
r 621
 
7.4%
t 614
 
7.3%
n 533
 
6.3%
s 505
 
6.0%
l 479
 
5.7%
i 459
 
5.4%
h 291
 
3.4%
Other values (39) 2839
33.6%
Common
ValueCountFrequency (%)
617
68.9%
- 263
29.4%
. 5
 
0.6%
( 4
 
0.4%
) 4
 
0.4%
' 2
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9338
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 805
 
8.6%
a 675
 
7.2%
o 622
 
6.7%
r 621
 
6.7%
617
 
6.6%
t 614
 
6.6%
n 533
 
5.7%
s 505
 
5.4%
l 479
 
5.1%
i 459
 
4.9%
Other values (45) 3408
36.5%